jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Gabriel Rath | Wassja A. Kopp | Kai Leonhard
Source: ChemRxiv (preprint, 2021-02-24)
Field: Chemistry — Organic Chemistry

Coupled Anharmonic Thermochemistry from Stratified Monte-Carlo Integration This study presents CIMCI, a new semi-classical method for handling fully coupled anharmonicity in gas-phase thermodynamics that promises to be black-boxable, to beapplicable for all kinds of anharmonicity, and to scale better at higher dimensionality than other methods for handling gas-phase molecular anharmonicity. The methoddoes so by using automatically and recursively stratified, simultaneous Monte Carlo integration of multiple functions. For the small systems analyzed by this study, themethod’s anharmonic corrections match reference data better than those of other blackbox anharmonic methods, e.g. VPT2. This holds even when sampling with CIMCIis done with primitive force fields, e.g. UFF, while the competing methods are used with proper, comprehensive potentials, e.g. the M06-2X meta-hybrid DFT functional.With further refinements in Monte Carlo sampling efficiency, in the quality of fast potentials practical for Monte Carlo sampling, and in automatic detection of which stereoisomers should be included during sampling, CIMCI has the potential to be the ideal anharmonic treatment for larger molecules where the large number of conformersand the high dimensionality of coupled torsions present major difficulties for other, existing treatments for anharmonicity. Anharmonicity ; Monte Carlo method ; Curse of dimensionality ; Statistical physics ; Sampling (signal processing) ; Hybrid Monte Carlo ; Thermochemistry ; Physics ; Computer science ; Thermodynamics ; Mathematics ; Markov chain Monte Carlo ; Quantum mechanics ; Statistics ; Machine learning Chemical Thermodynamics and Molecular Structure ; Phase Equilibria and Thermodynamics ; Advanced Chemical Physics Studies
Authors: Elahe Abedi | Mohammad Javad Amiri | Mehran Sayadi
Source: Research Square (preprint, 2021-02-23)
Field: Chemistry — Organic Chemistry

The potential use of ultrasound-assisted bleaching in removing heavy metals and pigments from soybean oil using kinetic, thermodynamic and equilibrium modeling: Linear and nonlinear approach and error analysis Abstract In this research, the sorption behavior (kinetic, isotherm and thermodynamic modeling) of heavy metals (Cu (II) and Fe (II)) and pigments (carotenoid and chlorophyll) on activated bentonite clay was investigated for soybean oil under industrial (IBM) and ultrasonic bleaching method (UBM). The results indicated that a nonlinear fitting approach with a higher coeﬃcient of determination (R 2 ) and lower Chi-square (χ 2 ) values was more appropriate to estimate kinetic and isotherm parameters than the linear fitting approach. The adsorption of metal ions and pigments on activated bentonite clay under UBM was quite well by the pseudo-ﬁrst-order model. In both bleaching methods, the equilibrium adsorption data follows the Freundlich isotherm model, presenting the sorption occurrence tends to be on a heterogeneous surface by multi-layer adsorption. The results indicated that the adsorption thermodynamics was endothermic nature and the process was spontaneous between 35 and 65 ˚C. Endothermic process ; Sorption ; Adsorption ; Freundlich equation ; Chemistry ; Thermodynamics ; Bentonite ; Kinetic energy ; Metal ions in aqueous solution ; Metal ; Chemical engineering ; Physical chemistry ; Organic chemistry Edible Oils Quality and Analysis ; Dye analysis and toxicity ; Spectroscopy and Chemometric Analyses
Authors: Ali Khumaidi | Yohanes Aris Purwanto | Heru Sukoco | Sony Hartono Wijaya
Source: ILKOM Jurnal Ilmiah (article, 2021-08-08)
Field: Chemistry — Analytical Chemistry

Effects of spectral transformations in support vector machine on predicting 'Arumanis' mango ripeness using near-infrared spectroscopy One of the challenges of exporting Arumanis mangoes is their accurate grading ability because the mangoes do not change color during ripening. Near-Infrared (NIR) spectroscopy is a non-destructive method for detecting the internal ripeness of fruit which is quite reliable. However, NIR absorbance bands are often nonspecific, extensive, and overlapping. Although SVM modeling is quite good in performance, it can still be improved by spectral transformation. In this study, 11 spectral transformation operations were compared with their combinations to find the best input model. Spectral transformation operations include SAVGOL, RNV, BASELINE, MSC, EMSC, NORML, CLIP, RESAMPLE, DETREND, SNV, and LSNV. In the 2 class classification model, the highest accuracy is obtained using RNV and SAVGOL. The prediction model for SSC content with the best MSE value uses 3 combinations of spectral transformation operations, namely DETREND, LSNV, and SAVGOL with parameter values: 'deriv_order': 0, 'filter_win': 31, 'poly_order': 6. As for the prediction model of mango hardness with The best MSE value uses 2 combinations of spectral transformation operations, namely LSNV and SAVGOL with parameter values: deriv_order ': 0,' filter_win ': 15,' poly_order ': 6. Ripeness ; Transformation (genetics) ; Mathematics ; Near-infrared spectroscopy ; Filter (signal processing) ; Ripening ; Absorbance ; Biological system ; Computer science ; Chemistry ; Optics ; Physics ; Chromatography ; Food science ; Computer vision Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Postharvest Quality and Shelf Life Management
Authors: Aditya G. Manjunath | Sabahudin Vrtagić | Fatih Doğan | Milan Đorđević | Mileta Žarković | Jasmin Kevrić | Goran Dobrić
Source: Instrumentation Mesure Métrologie (article, 2021-08-31)
Field: Materials Science — Materials Chemistry

Machine Learning MOSA Monitoring System This research paper deals with the problem of Metal-Oxide Surge Arrester (MOSA) condition monitoring and a new methodology in surge arrester monitoring and diagnostics is presented. A machine learning algorithm (back propagation regression) is used to estimate the non-linearity coefficient of the surge arrester, based on operating voltage and leakage current of the arrester. Using a simulated system, this research investigates the possibility of application and efficiency of machine learning. It is shown that the applied learning algorithm results are competitive with the model results parameters calculated as R2 = 0.999 and mean absolute real error computed as 0.005 which has shown that the proposed model can be used for MOSA monitoring and diagnostic purposes. Lightning arrester ; Surge arrester ; Engineering ; Voltage ; Reliability engineering ; Computer science ; Electrical engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Electrical Fault Detection and Protection
Authors: N. M'zali
Source: SPIRE - Sciences Po Institutional REpository (preprint, 2021-06-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Modélisation de l'effet de la découpe sur les propriétés magnétiques locales des aciers électriques et implantation dans un code éléments finis Cette thèse porte sur l’impact du processus de poinçonnage mécanique sur les propriétés magnétiques des matériaux qui composent les machines électriques. Le modèle anhystérétique de Sablik qui est basé sur une approche scalaire du couplage magnéto-mécanique a été considéré avec certaines modifications. Le modèle permet de décrire à la fois le couplage magnéto-élastique et magnéto-plastique. Le processus d'identification est réalisé à l'aide de courbes d’aimantations mesurées sous différentes contraintes élastiques et déformations plastiques. Le modèle prenant directement en compte la déformation plastique, une simulation de processus de poinçonnage mécanique a été réalisée à l'aide du logiciel ABAQUS pour définir la distribution de la déformation plastique sur le bord de coupe. Une simulation éléments finis d'une machine électrique synchrone incluant l'effet du poinçonnage a montré la dégradation de l’induction magnétique au niveau des bords de coupe et une augmentation des pertes fer d'environ 38%. Enfin, les résultats obtenus à partir de la simulation magnéto-mécanique ont été étudiés en termes de méthodes utilisées pour considérer la distribution de la déformation plastique dans le calcul numérique. Deux exemples ont été étudiés : une tôle d'acier et une dent d'une machine électrique. Il a été montré que le profil de dégradation défini par la valeur moyenne de la déformation en fonction de la distance au bord de coupe ne reflète pas la distribution réelle de la déformation plastique. Un ajustement de la méthode de calcul a été proposé. Finite element method ; Computation ; Code (set theory) ; Mechanical engineering ; Structural engineering ; Computational science ; Computer science ; Engineering ; Algorithm ; Programming language Magnetic Properties and Applications ; Induction Heating and Inverter Technology ; Electric Power Systems and Control
Authors: Wanying Huang | Haihong Jia | JunYan Luo
Source: Preprints.org (preprint, 2021-11-22)
Field: Chemistry — Organic Chemistry

Study on Dynamics and Cluster Analysis between Carbon-based Nanoparticles and Amino Acids We research the interaction between six representative carbon-based nanoparticles (CBNs) and 20 standard amino acids through all-atom molecular dynamics simulations. The six carbon-based nanoparticles are fullerene(C60), CNT55L3, CNT1010L3, CNT1515L3, CNT2020L3, and two-dimensional-graphene(Graphene33). Their curvatures decrease sequentially, and all of CNT are single-walled carbon nanotubes. We have observed that as the curvature of CBNs decreases, the adsorption effect of 20 amino acids with them has an increasing trend. In addition, we also used multi-dimensional clustering to analyze the adsorption effects of 20 amino acids on six carbon-based nanoparticles. We observed that the &amp;pi;-&amp;pi; interaction still plays an extremely important role in the adsorption of amino acids on carbon-based nanoparticles. Individual long-chain amino acids and &amp;ldquo;Benzene-like&amp;rdquo; Pro also have a strong adsorption effect with carbon-based nanoparticles. Nanoparticle ; Amino acid ; Carbon fibers ; Adsorption ; Fullerene ; Molecular dynamics ; Graphene ; Carbon nanotube ; Chemistry ; Cluster (spacecraft) ; Carbon Nanoparticles ; Carbon atom ; Nanotechnology ; Computational chemistry ; Materials science ; Chemical engineering ; Organic chemistry ; Biochemistry ; Computer science Fullerene Chemistry and Applications ; Carbon Nanotubes in Composites ; Graphene and Nanomaterials Applications
Authors: Xiaorong Zheng | Julius Krause | Benedikt Fischer | Robin Gruna | Reinhard Töpfer | Anna Kicherer
Source:  (article, 2021-03-17)
Field: Chemistry — Analytical Chemistry

Phenoliner 2.0: RGB and near-infrared (NIR) image acquisition for an efficient phenotyping in grapevine research In grapevine research, phenotyping needs to be done for different traits such as abiotic and biotic stress. This phenotypic data acquisition is very time-consuming and subjective due to the limitation of manual visual estimation. Sensor-based approaches showed an improvement in objectivity and throughput in the past. For example, the ‘Phenoliner’ a phenotyping platform, based on a modified grape harvester, is equipped with two different sensor systems to acquire images in the field. It has so far been used in grapevine research for different research questions to test and apply different sensor systems. However, the driving speed for data acquisition has been limited to 0.5 - 1 km/h due to capacity of image acquisition frequency and storage. Therefore, a faster automatic data acquisition with high objectivity and precision is desirable to increase the phenotyping efficiency. To this aim, in the present study a prism-based simultaneous multispectral camera system was installed in the tunnel of the ‘Phenoliner’ with an artificial broadband light source for image acquisition. It consists of a visible color channel from 400 to 670 nm, a near infrared (NIR) channel from 700 to 800 nm, and a second NIR channel from 820 to 1,000 nm. Compared to the existing camera setup, image recording could be improved to at least 10 images per second and a driving speed of up to 6 km/h. Each image is geo-referenced using a real-time-kinematic (RTK)- GPS system. The setup of the sensor system was tested on seven varieties (Riesling, Pinot Noir, Chardonnay, Dornfelder, Dapako, Pinot Gris, and Phoenix) with and without symptoms of biotic stress in the vineyards of Geilweilerhof, Germany. Image analysis aims to segment images into four categories: trunk, cane, leaf, and fruit cluster to further detect the biotic stress status in these categories. Therefore, images have been annotated accordingly and first results will be shown. RGB color model ; Computer science ; Artificial intelligence ; Computer vision ; Image (mathematics) ; Remote sensing ; Geography Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Advanced Chemical Sensor Technologies
Authors: Jieyun Bai | Yaosheng Lu | Yijie Zhu | Huijun Wang | Dechun Yin | Henggui Zhang | Diego Franco | Jichao Zhao
Source: Preprints.org (preprint, 2021-06-22)
Field: Materials Science — Materials Chemistry

Understanding PITX2-dependent Atrial Fibrillation Mechanisms through Computational Models Atrial fibrillation (AF) is a common arrhythmia. Better prevention and treatment of AF are needed to reduce AF-associated morbidity and mortality. Several major mechanisms cause AF in patients, including a genetic predisposition to develop AF. Genome-wide association studies have identified genetic variants associated with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene coding for the homeobox transcription PITX2. Because of the inherent complexity of the human heart, experimental and basic research on PITX2-dependent AF is not sufficient for understanding atrial functional proprieties. Linking PITX2 to ion channels, cells, tissues, atria and the whole heart, computational models are necessary for achieving a quantitative understanding of atrial structure and function in PITX2-dependent AF. Computational approaches are used to capture all that we know about PITX2-dependent AF and to develop improved therapies. In the present review, we discuss advances in atrial modelling and focus on the mechanistic links between PITX2 and AF. Challenges in applying models for improving patient health are described, as well as a summary of future perspectives. PITX2 ; Atrial fibrillation ; Homeobox ; Chromosome ; Bioinformatics ; Medicine ; Computational biology ; Internal medicine ; Cardiology ; Computer science ; Transcription factor ; Neuroscience ; Biology ; Gene ; Genetics Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Saleh Hassan | Sirisha Kamireddy | M.P. Yutkin | Clayton J. Radke | Tadeusz W. Patzek
Source:  (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Approximating Irreversible Asphaltene Adsorption to Screen IOR Candidates Summary After drainage of brine-filled rock pores with an asphaltenic crude oil, the wettability state of a sandstone or limestone subjected to a high capillary pressure eventually changes from strongly water-wet to mixed-wet. A partial reversal of this mostly irreversible change of reservoir rock wettability is the condition necessary to increasing field-scale recovery of asphaltenic crudes. In this work, we propose asphaltene molecule proxies that possess many asphaltene properties and satisfy reservoir adsorption conditions. We quantify the irreversible adsorption of these analogs with carboxylic, amino, or sulfate groups onto the silica using a quartz crystal microbalance with dissipation (QCM-D). We explore conditions for desorption of the irreversibly adsorbed analogs. We use aqueous-soluble functionalized dextran polymers of variable chain length as asphaltene analogs. Adsorption was studied in brines with varying salts and pH. QCM-D results reveal that positively charged ammonia-functionalized poly-dextrans adsorb on silica irreversibly regardless of chain length and brine composition. However, sufficiently long chains and the presence of calcium ions are required for negatively charged sulfate- and carboxylate-modified poly-dextrans to adsorb irreversibly onto silica surface. Such a phenomenon is explained by calcium ion bridging of two negatively charged moieties. Experiment duration is found to be important for irreversible adsorption as well. After the polymers have irreversibly adsorbed to silica, we attempt to desorb them by changing the brine composition. Desorption tests included combinations of 10, 100 and 300 mM of NaCl, KCl and CsCl. Preliminary results suggest that dextran polymers adsorbed via the bridging mechanism (i.e., sulfate- and carboxylate-modified) desorb using salt solutions with monovalent cations of potassium and cesium in obedience to the Hofmeister series. A similar result, but to a lesser extent, applies to ammonia-functionalized poly-dextrans yielding far less desorption. In summary, positively charged amines adsorb irreversibly on the negatively charged silica surface. However, three factors are important to achieve irreversible adsorption of carboxylates and sulfates: a sufficient chain length, presence of calcium ions, and time. For monovalent cations, desorption efficiency seems to follow the Hofmeister series but to different extents depending on the adsorption mechanism. Adsorption ; Asphaltene ; Desorption ; Quartz crystal microbalance ; Wetting ; Chemistry ; Brine ; Chemical engineering ; Carboxylate ; Aqueous solution ; Polymer ; Inorganic chemistry ; Organic chemistry Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: R.V. Liutyi
Source: Theory and practice of metallurgy (article, 2021-02-22)
Field: Materials Science — General Materials Science

Analytical method of calculation of thermal fields of cast parts during crystallization The aim of the work is to create a mathematical method that allows to calculate the distribution of thermal fields in cast parts during crystallization using a system of analytical formulas. During the calculations, a combination of known analytical formulas GF was used. Balandin, AY Weinik, S. Schwartz with their own original mathematical solutions created on the basis of the analysis of thermophysical processes in castings in the process of their crystallization. Computer simulation of thermal fields using the LVMFlow program was used to compare the results. According to the created mathematical method, examples of calculation of thermal fields for two castings made of steel 25L of hollow cylindrical shape, the wall thickness of which is 100 mm and 4 mm, respectively, are given. Calculations were performed for the conditions of crystallization of castings in a single sand form. The comparison of results of calculations by the developed method and with use of the existing software is presented. For the first time, based on our own mathematical and thermophysical developments, a comprehensive calculation method for determining the thermal field of the casting during crystallization and cooling was developed. casting. The technique is expressed in a number of analytical formulas, each of which describes a specific thermal process that occurs in the casting. This takes into account the features of the casting configuration. The created complex method of calculation of thermal fields of cast parts is a mathematical basis for determining the thermal fields of molds and rods, which allows to predict their properties and select the optimal molding materials. The created technique can also be offered as a mathematical basis for refining applied computer programs for foundry production. CASTING, TEMPERATURE, THERMAL FIELD, COOLING DYNAMICS, COOLING DURATION, MATHEMATICAL LAW, COLORING FRONT, CALCULATION Crystallization ; Thermal ; Casting ; Process (computing) ; Field (mathematics) ; Basis (linear algebra) ; Work (physics) ; Materials science ; Mathematical model ; Mechanical engineering ; Mechanics ; Thermodynamics ; Computer science ; Mathematics ; Metallurgy ; Geometry ; Physics ; Engineering Material Properties and Applications ; Materials Engineering and Processing ; Diverse Industrial Engineering Technologies
Authors: Simona Condaragiu | Nicolae Lucanu | Philipp Lebhardt | Jens Langejuergen | Iulian B. Ciocoiu
Source: Buletinul Institutului Politehnic din Iaşi. Secţia Electrotehnică. Energetică. Electronică (article, 2021-03-01)
Field: Chemistry — Spectroscopy

Preprocessing Methods for GC-IMS Image Analysis Abstract The paper presents a cascade of preprocessing procedures aiming at enhancing the quality of images generated by gas-chromatography ion mobility spectrometers (GC-IMS). The methods successfully eliminate the Reactant Ion Peak (RIP) lines, while additionally filtering out noisy components. The resulting images enable better localization and matching of the peaks associated with the presence of distinct analytes in the samples under study. Preprocessor ; Analyte ; Ion-mobility spectrometry ; Computer science ; Artificial intelligence ; Cascade ; Chromatography ; Pattern recognition (psychology) ; Image (mathematics) ; Mass spectrometry ; Chemistry ; Analytical Chemistry (journal) Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies
Authors: Umut Çalışkan | Saadettin KAHRAMAN | Talha KOÇYİĞİT
Source: International Scientific and Vocational Studies Journal (article, 2021-12-14)
Field: Materials Science — Materials Chemistry

Multi-Scale Modeling of Graphene/Polymer Nanocomposites-Molecular Interfacial Interactions This paper presents a multi-scale modeling approach involving interfacial interactions to predict the elastic properties and mechanical behavior of single-layer graphene-reinforced nanocomposites under tension load. A multi-scale model was developed using the finite element method of the tripartite structure consisting of graphene in epoxy, the interfacial region and their Van Der Walls interactions. The effect of graphene chirality was investigated by proposing a methodology of graphene-Van Der Walls interactions-polymer with determined geometric dimensions. Parametric modeling was performed to model the interactions between Van Der Walls, graphene and interface material atoms using the finiteelement method with molecular mechanics approach. Numerical analysis of graphene nanoparticles by embedding them in an epoxy with their real dimensions is not an appropriate task today. In particular, it is not possible to analyze these real graphene nanoparticles as multiple by randomly dispersing them in the epoxy polymer. Therefore, in this research, a model was developed to overcome this problem and to investigate the effect of molecular interactions on loads in different axes. The results show that graphene nanocomposites in armchair geometry give higher stress values and behave more rigidly. As the volume ratio increases, the mechanical performances increase. It is seen that the graphene direction is much stronger than the thickness direction. It is clear that the volume ratio effect in the thickness direction has a slight effect on the tensile behavior. Graphene ; Materials science ; Epoxy ; Polymer ; Polymer nanocomposite ; Composite material ; Nanocomposite ; Molecular dynamics ; Ultimate tensile strength ; Nanotechnology ; Computational chemistry ; Chemistry Graphene research and applications ; Carbon Nanotubes in Composites ; Fiber-reinforced polymer composites