jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Gustavo Navarro | Jorge Nájera | Jorge Torres | Marcos Blanco | Miguel Santos-Herrán | Marcos Lafoz
Source: Energies (article, 2020-03-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Development and Experimental Validation of a Supercapacitor Frequency Domain Model for Industrial Energy Applications Considering Dynamic Behaviour at High Frequencies Supercapacitors, one of the most promising energy storage technologies for high power density industrial applications, exchange the energy mostly through power electronic converters, operating under high frequency components due to the commutation. The high frequency produces important effects on the performance of the supercapacitors in relation to their capacitance, inductance and internal resistance (ESR). These parameters are fundamental to evaluate the efficiency of this energy storage system. The aim of the paper is to obtain an accurate model of two supercapacitors connected in series (functional and extrapolated unit) to represent the frequency effects for a wide range of frequencies. The methodology is based on the definition of an appropriate equivalent electric circuit with voltage dependance, obtaining their parameters from experimental tests, carried out by means of electrochemical impedance spectroscopy (EIS) and the use of specific software tools such as EC-Lab® and Statgraphics Centurion®. The paper concludes with a model which reproduces with accuracy both the frequency response of the model BCAP3000 supercapacitors, provided by the manufacturer, and the experimental results obtained by the authors. Supercapacitor ; Capacitance ; Energy storage ; Converters ; Inductance ; Electrical impedance ; Electronic engineering ; Frequency domain ; Power density ; Power (physics) ; Equivalent circuit ; Voltage ; Electrical engineering ; Computer science ; Engineering ; Physics ; Electrode Supercapacitor Materials and Fabrication ; Electric and Hybrid Vehicle Technologies ; Advanced Battery Technologies Research
Authors: Xiaoyan Ouyang | Zicheng Lu | Yuling Hu | Zenghui Xie | Gongke Li
Source: Journal of Separation Science (review, 2020-12-11)
Field: Chemistry — Analytical Chemistry

Research progress on sample pretreatment methods for migrating substances from food contact materials Excessive absorption of migrating substances from food contact materials can affect human health. Thus, it is essential to analyze the migration of contaminant from food contact materials. However, comprehensive analysis has been challenged by low concentration of migrating substances, manifold and complex matrix interference of food contact materials. Therefore, appropriate sample pretreatment methods should be applied before instrumental detection, which is essential to improve the analytical efficiency, sensitivity, and reliability. This paper systematically reviews the development of sample pretreatment methods for analysis of migrating substances from food contact materials in the past decade. To extract volatile and semi-volatile substances, headspace extraction, headspace solid phase microextraction, and purge and trap technique are discussed. For non-volatile substances, solid-liquid extraction and field-assisted extraction are usually used to extract them from food contact materials, while liquid-liquid extraction, solid phase extraction, and their corresponding microextraction techniques play important roles on enrichment process. In addition, new progress in developments of sample pretreatment methods of food contact materials is summarized, covering new devices, specific adsorbents, and sample preparation methods for rapid detection. An outlook of future prospect of sample pretreatment, especially for non-targeted analysis of non-intentionally added substances is briefly discussed. Food contact materials ; Sample preparation ; Solid phase extraction ; Extraction (chemistry) ; Solid-phase microextraction ; Complex matrix ; Chromatography ; Matrix (chemical analysis) ; Chemistry ; Process engineering ; Materials science ; Food packaging ; Gas chromatography–mass spectrometry ; Mass spectrometry ; Food science Analytical chemistry methods development ; Effects and risks of endocrine disrupting chemicals ; Advanced Chemical Sensor Technologies
Authors: Vo-Nguyen Tuyet-Doan | Tien‐Tung Nguyen | Minh-Tuan Nguyen | Jong-Ho Lee | Yong‐Hwa Kim
Source: Energies (article, 2020-04-23)
Field: Materials Science — Materials Chemistry

Self-Attention Network for Partial-Discharge Diagnosis in Gas-Insulated Switchgear Detecting, measuring, and classifying partial discharges (PDs) are important tasks for assessing the condition of insulation systems used in different electrical equipment. Owing to the implementation of the phase-resolved PD (PRPD) as a sequence input, an existing method that processes sequential data, e.g., the recurrent neural network, using a long short-term memory (LSTM) has been applied for fault classification. However, the model performance is not further improved because of the lack of supporting parallel computation and the inability to recognize the relevance of all inputs. To overcome these two drawbacks, we propose a novel deep-learning model in this study based on a self-attention mechanism to classify the PD patterns in a gas-insulated switchgear (GIS). The proposed model uses a self-attention block that offers the advantages of simultaneous computation and selective focusing on parts of the PRPD signals and a classification block to finally classify faults in the GIS. Moreover, the combination of LSTM and self-attention is considered for comparison purposes. The experimental results show that the proposed method achieves performance superiority compared with the previous neural networks, whereas the model complexity is significantly reduced. Switchgear ; Computer science ; Block (permutation group theory) ; Computation ; Artificial intelligence ; Partial discharge ; Artificial neural network ; Fault (geology) ; Sequence (biology) ; Pattern recognition (psychology) ; Relevance (law) ; Machine learning ; Data mining ; Voltage ; Algorithm ; Engineering ; Mathematics ; Electrical engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Elevator Systems and Control
Authors: Xiaoyang Ni | Zheng Wu | Wenlong Zhang | Kaihua Lu | Yanming Ding | Shaohua Mao
Source: Polymers (article, 2020-08-05)
Field: Materials Science — Polymers and Plastics

Energy Utilization of Building Insulation Waste Expanded Polystyrene: Pyrolysis Kinetic Estimation by a New Comprehensive Method Expanded polystyrene (EPS) has excellent thermal insulation properties and is widely applied in building energy conservation. However, these thermal insulation materials have caused numerous fires because of flammability. Pyrolysis is necessary to support combustion, and more attention should be paid to the pyrolysis characteristics of EPS. Moreover, pyrolysis is considered to be an effective method for recycling solid waste. Pyrolysis kinetics of EPS were analyzed by thermogravimetric experiments, both in nitrogen and air atmospheres. A new method was proposed to couple the Flynn-Wall-Ozawa model-free method and the model-fitting method called the Coats-Redfern as well as the particle swarm optimization (PSO) global algorithm to establish reaction mechanisms and their corresponding kinetic parameters. It was found that the pyrolysis temperature of EPS was concentrated at 525-800 K. The activation energy of EPS in nitrogen was about 163 kJ/mol, which was higher than that in air (109.63 kJ/mol). Furthermore, coupled with Coats-Redfern method, reaction functions <i>g(α) = 1 - (1 - α)<sup>3</sup></i> and <i>g(α) = 1 - (1 - α)<sup>1/4</sup></i> should be responsible for nitrogen and air reactions, respectively. The PSO algorithm was applied to compute detailed pyrolysis kinetic parameters. Kinetic parameters could be used in further large-scale fire simulation and provide guidance for reactor design. Polystyrene ; Pyrolysis ; Materials science ; Kinetic energy ; Expanded polystyrene ; Waste management ; Estimation ; Environmental science ; Process engineering ; Composite material ; Polymer ; Engineering Flame retardant materials and properties ; Fire dynamics and safety research ; Thermochemical Biomass Conversion Processes
Authors: Kenzo Hiraoka | Osamu Ariyada | Dilshadbek T. Usmanov | Lee Chen-Chen | Satoshi Ninomiya | Kentaro Yoshimura | Sén Takeda | Yu Zhang | Mridul Kanti Mandal | Hiroshi Wada | Stephanie Rankin‐Turner | Hiroshi Nonami
Source: Mass Spectrometry (article, 2020-10-23)
Field: Chemistry — Spectroscopy

Probe Electrospray Ionization (PESI) and Its Modified Versions: Dipping PESI (dPESI), Sheath-Flow PESI (sfPESI) and Adjustable sfPESI (ad-sfPESI) In 2007, probe electrospray ionization/mass spectrometry (PESI/MS) was developed. In this technique, the needle is moved down along a vertical axis and the tip of the needle touched to the sample. After capturing the sample at the needle tip, the needle is then moved up and a high voltage is applied to the needle at the highest position to generate electrospray. Due to the discontinuous sampling followed by the generation of spontaneous electrospray, sequential and exhaustive electrospray takes place depending on the surface activity of the analytes. As modified versions of PESI, dipping PESI (dPESI), sheath-flow PESI (sfPESI) and adjustable sfPESI (ad-sfPESI) have been developed. These methods are complementary to each other and they can be applicable to surface and bulk analysis of various biological samples. In this article, the characteristics of these methods and their applications to real samples will be reviewed. Electrospray ; Electrospray ionization ; Mass spectrometry ; Chemistry ; Analytical Chemistry (journal) ; Chromatography ; Materials science Mass Spectrometry Techniques and Applications ; Microfluidic and Capillary Electrophoresis Applications ; Analytical Chemistry and Chromatography
Authors: Haiyi Bian | Hua Yao | Guohua Lin | Yinshan Yu | Ruiqiang Chen | Xiaoyan Wang | Rendong Ji | Xiao Yang | Tiezhu Zhu | Y. L. Ju
Source: IEEE photonics journal (article, 2020-02-18)
Field: Chemistry — Analytical Chemistry

Multiple Kinds of Pesticides Detection Based on Back-Propagation Neural Network Analysis of Fluorescence Spectra Fluorescence spectroscopy attracted more and more attention in pesticide residue detection field because of its advantages of non-destructive, non-contact, high speed and no requirement of complex pre-process procedure. However, given that the concentration of the pesticide detected via fluorescence spectroscopy is calculated in accordance with the Beer-Lambert law, this method can only be used to detect samples containing a single kind of pesticide or several kinds of pesticides with completely different fluorescence which is not in accordance with practical cases. In this article, to overcome this disadvantage, back-propagation (BP) neural network algorithm was introduced to detect multiple kinds of pesticides via fluorescence spectroscopy. The results from four kinds of pesticides which are usually used for fruits and vegetables indicated the effectiveness of BP neural network algorithm. Pesticide ; Fluorescence ; Artificial neural network ; Fluorescence spectroscopy ; Spectroscopy ; Biological system ; Backpropagation ; Computer science ; Pesticide residue ; Analytical Chemistry (journal) ; Chemistry ; Artificial intelligence ; Environmental chemistry ; Optics ; Physics ; Ecology ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Algorithms and Applications
Authors: Michał Maciusowicz | Grzegorz Psuj
Source: Sensors (article, 2020-01-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Time-Frequency Analysis of Barkhausen Noise for the Needs of Anisotropy Evaluation of Grain-Oriented Steels The paper presents a new approach to obtain information on magnetic anisotropy in Si-Fe grain oriented ferromagnetic steel based on the observation of the magnetic Barkhausen noise (MBN). Until now, in the literature one can only notice the MBN study of magnetic anisotropy in steels carried out in a single time or frequency domain. However, due to the observed high variability of the dynamics of the MBN phenomenon over its occurrence period, depending on the steel properties, the idea of utilization of combined time and frequency representations to obtain new or supplementary information arises. For this purpose, the MBN phenomenon was observed in various directions for steels with oriented magnetic properties. Then, using the short-time Fourier transform, time-frequency (<i>TF</i>) distributions were determined and features vectors enabling the quantification of crucial information were determined. Before performing the final experiments, a series of tests were carried out for different measuring conditions. As a result, it was possible to adjust the conditions enabling us to obtain the highest possible sensitivity for MBN and discrimination level between directional properties in the material. Then, an algorithm of detailed analysis and division of the <i>TF</i> representation into subranges was proposed, enabling the extraction of more detailed information about the phenomena occurring during the magnetization process. This allowed us to clearly indicate and then separate three areas of MBN main activity. Finally, the obtained angular distributions of selected features were presented and discussed, and further conclusions were given. Barkhausen effect ; Anisotropy ; Frequency domain ; Ferromagnetism ; Sensitivity (control systems) ; Materials science ; Noise (video) ; Magnetic domain ; Grain boundary ; Magnetization ; Computational physics ; Biological system ; Computer science ; Statistical physics ; Electronic engineering ; Condensed matter physics ; Physics ; Magnetic field ; Engineering ; Mathematics ; Metallurgy ; Mathematical analysis ; Artificial intelligence ; Optics Magnetic Properties and Applications ; Non-Destructive Testing Techniques ; Microstructure and Mechanical Properties of Steels
Authors: Sandrine Galtier | Clément Pivard | Patrick Rairoux
Source: Remote Sensing (article, 2020-10-20)
Field: Chemistry — Spectroscopy

Towards DCS in the UV Spectral Range for Remote Sensing of Atmospheric Trace Gases The development of increasingly sensitive and robust instruments and new methodologies are essential to improve our understanding of the Earth’s climate and air pollution. In this context, Dual-Comb spectroscopy (DCS) has been successfully demonstrated as a remote laser-based instrument to probe infrared absorbing species such as greenhouse gases. We present here a study of the sensitivity of Dual-Comb spectroscopy to remotely monitor atmospheric gases focusing on molecules that absorb in the ultraviolet domain, where the most reactive molecules of the atmosphere (OH, HONO, BrO...) have their highest absorption cross-sections. We assess the achievable signal-to-noise ratio (SNR) and the corresponding minimum absorption sensitivity of DCS in the ultraviolet range. We propose a potential light source for remote sensing UV-DCS and discuss the degree of immunity of UV-DCS to atmospheric turbulences. We show that the characteristics of the currently available UV sources are compatible with the unambiguous identification of UV absorbing gases by UV-DCS. Trace gas ; Ultraviolet ; Context (archaeology) ; Infrared ; Absorption (acoustics) ; Remote sensing ; Atmosphere (unit) ; Spectroscopy ; Environmental science ; Materials science ; Optoelectronics ; Optics ; Physics ; Atmospheric sciences ; Meteorology Spectroscopy and Laser Applications ; Advanced Fiber Laser Technologies ; Atmospheric Ozone and Climate
Authors: Simon E. F. Spencer | Alison Rodger
Source: Analytical Methods (article, 2020-12-08)
Field: Chemistry — Spectroscopy

Bayesian inference assessment of protein secondary structure analysis using circular dichroism data – how much structural information is contained in protein circular dichroism spectra? Circular dichroism spectroscopy is an important tool for determining the structural characteristics of biomolecules, particularly the secondary structure of proteins. In this paper we propose a Bayesian model that estimates the covariance structure within a measured spectrum and quantifies the uncertainty associated with the inferred secondary structures and characteristic spectra associated with each secondary structure type. Furthermore, we used tools from Bayesian model selection to determine the best secondary structure classification scheme and illustrate a technique for comparing whether or not two or more measured protein spectra share the same secondary structure. Our findings suggest that it is not possible to identify more than 3 distinct secondary structure classes from CD spectra above 175 nm. The inclusion of data from wavelengths between 175 and 200 nm did not substantially affect the ability to determine secondary structure fractions. Circular dichroism ; Protein secondary structure ; Inference ; Bayesian probability ; Vibrational circular dichroism ; Spectral line ; Chemistry ; Biological system ; Physics ; Mathematics ; Crystallography ; Computer science ; Statistics ; Artificial intelligence ; Biology ; Biochemistry Molecular spectroscopy and chirality ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Zeynep Mine Şenol | Selçuk Şimşek | Halil İbrahim Ulusoy | Ayyaz Mahmood | Savaş Kaya
Source: Polymer Testing (article, 2020-04-27)
Field: Chemistry — Inorganic Chemistry

Insight from adsorption properties of Xylidyl Blue embedded hydrogel for effective removal of uranyl: Experimental and theoretical approaches Uranyl ; Adsorption ; Endothermic process ; Freundlich equation ; Langmuir ; Aqueous solution ; Materials science ; Diffusion ; Langmuir adsorption model ; Ion ; Analytical Chemistry (journal) ; Reaction rate constant ; Chemical engineering ; Inorganic chemistry ; Nuclear chemistry ; Chemistry ; Physical chemistry ; Kinetics ; Thermodynamics ; Chromatography ; Organic chemistry Radioactive element chemistry and processing ; Analytical chemistry methods development ; Analytical Chemistry and Sensors
Authors: Michal Jablonský | Veronika Majová | Jozef Šíma | Katarína Hroboňová | Anna Lomenová
Source: Crystals (article, 2020-03-19)
Field: Chemistry — Analytical Chemistry

Involvement of Deep Eutectic Solvents in Extraction by Molecularly Imprinted Polymers—A Minireview Substantial research activity has been focused on new modes of extraction and refining processes during the last decades. In this field, coverage of the recovery of bioactive compounds and the role of green solvents such as deep eutectic solvents (DESs) also gradually increases. A specific field of DESs involvement is represented by molecularly imprinted polymers (MIPs). The current state and prospects of implementing DESs in MIPs chemistry are, based on the accumulated experimental data so far, evaluated and discussed in this minireview. Molecularly imprinted polymer ; Eutectic system ; Extraction (chemistry) ; Polymer ; Chemistry ; Nanotechnology ; Materials science ; Chromatography ; Organic chemistry ; Catalysis ; Selectivity Analytical chemistry methods development ; Ionic liquids properties and applications ; Extraction and Separation Processes
Authors: Braja Gopal Bag | Abir Chandan Barai
Source: RSC Advances (article, 2020-01-01)
Field: Materials Science — Biomaterials

Self-assembly of naturally occurring stigmasterol in liquids yielding a fibrillar network and gel Stigmasterol, a naturally occurring 6-6-6-5 monohydroxy phytosterol, was extracted from the leaves of Indian medicinal plant <i>Roscoea purpurea</i>, commonly known as Kakoli. In continuation of our studies on the self-assembly properties of naturally occurring terpenoids, herein, we report the first self-assembly properties of this phytosterol in different organic liquids. The molecule self-assembled in organic liquids yielding supramolecular gels in most of the liquids studied <i>via</i> the formation of fibers and belt-like architechtures of nano-to micrometer diameter. Characterization of the self-assemblies carried out by using scanning electron microscopy, transmission electron microscopy, atomic force microscopy, optical microscopy, FTIR and X-ray diffraction studies indicated fibrillar network and belt-like structures. A model for the self-assembly of stigmasterol has been proposed based on molecular modeling studies, X-ray diffraction data and FTIR studies. Rheology studies indicated that the gels were of high mechanical strength. Fluorophores such as rhodamine B, carboxy fluorescein including the anticancer drug doxorubicin could be loaded in the gels. Moreover, release of the loaded fluorophores including the drug has also been demonstrated from the gel phase into aqueous medium. Stigmasterol ; Supramolecular chemistry ; Transmission electron microscopy ; Self-assembly ; Chemical engineering ; Fourier transform infrared spectroscopy ; Materials science ; Rhodamine B ; Chemistry ; Micrometer ; Scanning electron microscope ; Phytosterol ; Crystallography ; Molecule ; Nanotechnology ; Organic chemistry ; Chromatography ; Composite material ; Optics Supramolecular Self-Assembly in Materials ; Lipid Membrane Structure and Behavior ; Polydiacetylene-based materials and applications
Authors: I Bates | Éric Loranger | Bruno Chabot
Source: SN Applied Sciences (article, 2020-08-20)
Field: Materials Science — Biomaterials

Chitosan-PEO nanofiber mats for copper removal in aqueous solution using a new versatile electrospinning collector Adsorption ; Aqueous solution ; Sorption ; Electrospinning ; Nanofiber ; Chemical engineering ; Materials science ; Chitosan ; Langmuir adsorption model ; Copper ; Endothermic process ; Desorption ; Composite material ; Chemistry ; Polymer ; Organic chemistry ; Metallurgy Electrospun Nanofibers in Biomedical Applications ; Membrane Separation Technologies ; Graphene and Nanomaterials Applications
Authors: Qudsia Tabassam | Tahir Mehmood | Abdul Rauf Raza | Azmat Ullah | Farhan Saeed | Faqir Muhammad Anjum
Source: International Journal of Nanomedicine (article, 2020-09-01)
Field: Materials Science — Materials Chemistry

&lt;p&gt;Synthesis, Characterization and Anti-Cancer Therapeutic Potential of Withanolide-A with 20nm sAuNPs Conjugates Against SKBR3 Breast Cancer Cell Line&lt;/p&gt; Our findings provide a foundation to further progress how they can overcome cancer drug resistance by conjugating active drugs in combination with AuNPs through optimizing the effective drug concentration and removing the surface barrier. SKBR3 ; Drug delivery ; Dynamic light scattering ; Materials science ; Nanotechnology ; Colloidal gold ; Cancer cell ; Nanoparticle ; Cancer ; Medicine ; Human breast Nanoparticles: synthesis and applications ; Phytochemicals and Medicinal Plants ; Medicinal Plants and Neuroprotection
Authors: Alice Domenichini | Ilaria Casari | Peter V. Simpson | Nima Maheshkumar Desai | Lingfeng Chen | Christopher M. Dustin | Jeanne S. Edmands | Albert van der Vliet | Moosa Mohammadi | Massimiliano Massi | Marco Falasca
Source: Journal of Experimental & Clinical Cancer Research (article, 2020-12-01)
Field: Chemistry — Organic Chemistry

Rhenium N-heterocyclic carbene complexes block growth of aggressive cancers by inhibiting FGFR- and SRC-mediated signalling Our findings provide a basis for the development of rhenium-based chemotherapy agents with enhanced selectivity and limited side effects compared to standard platinum-based drugs. Rhenium ; Cancer research ; Zebrafish ; Cancer ; Pancreatic cancer ; Pharmacology ; Toxicity ; Chemistry ; In vivo ; Sorafenib ; Gemcitabine ; Medicine ; Internal medicine ; Biology ; Biochemistry ; Hepatocellular carcinoma Quinazolinone synthesis and applications ; Histone Deacetylase Inhibitors Research ; N-Heterocyclic Carbenes in Organic and Inorganic Chemistry