jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Allu Shanmukha Rao | N. Sumathi | N. Vasudev
Source: Power Research - A Journal of CPRI (article, 2023-03-15)
Field: Materials Science — Materials Chemistry

A Study on the Development of New Silicone based Polymeric Outdoor Insulator Material for Enhanced Properties Polymeric insulators have been increasingly popular in recent years as a result of their superior performance in contaminated environments due to their hydrophobic properties. However, research into the ageing condition of polymeric materials and their practicality for large-scale use is currently ongoing. Insulator deterioration is caused by environmental tracking and erosion factors. As insulators age, they develop immature failures and inconsistencies in their functioning. pollution performance of polymeric insulators is a vital factor in the quality and reliability of the power system. Over some time, dry band arcing can initiate the flashover and it causes degradation in the form of erosion and tracking. Polymeric insulators’ performance is heavily influenced by the constituent materials and their properties. There is a critical need to investigate innovative filler materials that can be combined with existing polymeric base materials to form composites. In this context the proposed research use silicone rubber as a base polymeric material, to which additives are added to produce three distinct composites by varying the filler concentration. Preliminary studies were made to evaluate the hydrophobicity, dielectric strength, hardness, specific gravity, tensile strength, ultimate elongation and tear strength properties of this HTV silicone rubbed-based composites by using ASTM standards and IEC 60587 requirements. Studies were also made by accelerated ageing on sample material by using the IPTE test. The results show substantial improvement in the electrical and ageing properties. Materials science ; Composite material ; Silicone rubber ; Silicone ; Ultimate tensile strength ; Tear resistance ; Context (archaeology) ; Arc flash ; Filler (materials) ; Durability ; Insulator (electricity) High voltage insulation and dielectric phenomena ; Engineering Applied Research ; Thermal Analysis in Power Transmission
Authors: Muhammad Reza Maulana Aliva | Nofi Yendri Sudiar | Hamdi Hamdi
Source: JURNAL TEKNOLOGI REAKTOR NUKLIR TRI DASA MEGA (article, 2023-07-28)
Field: Materials Science — Materials Chemistry

SYSTEMATIC LITERATURE REVIEW (SLR): NUCLEAR POWER PLANTS Nuclear Power Plant (NPP) is a thermal power plant using one or several nuclear reactors as its heat source. NPP uses radioactive materials such as uranium as the heat source by utilizing fission reactions. The fission reaction produces enormous heat energy. Currently, there are many studies on NPPs, ranging from technological developments to the environmental impact of the NPP itself. This study aims to identify research developments on nuclear power plants from around the world obtained from relevant international journals in 2017-2023. The method used in this study is the Systematic Literature Review (SLR) method. The SLR method is used to identify, review, evaluate, and conclude all available research with interesting topic areas, with specific relevant research questions. Data were obtained by searching journals with Harzing's Publish or Perish application from the Scopus journal database. There are 191 journals with the keyword " Nuclear Power Plant " obtained from the Scopus database. Then these journals are filtered by type of article and if the number of citations is more than 32, then 49 articles are obtained which will be reviewed. This SLR method shows the development of research on NPP in several developed countries that have been using this technology for a long time. In addition, research topics such as the Fukushima accident, fault diagnostics, and safety assessment are the most discussed topics in the research so that they can be used as a reference for countries that are developing NPP. Scopus ; Nuclear power plant ; Nuclear power ; Nuclear fission ; Computer science ; Publication ; Environmental science ; Nuclear physics ; Fission ; Political science ; Physics Graphite, nuclear technology, radiation studies
Authors: Hassan Abdolpour | Paweł Niewiadomski | Łukasz Sadowski | Arkadiusz Kwiecień
Source: U Porto Journal of Engineering (article, 2023-09-22)
Field: Materials Science — Ceramics and Composites

Design of an innovative self-compacting material modified with recycled steel fibers and spent equilibrium catalyst for ultra-high performance applications The main aim of the present study is to design an innovative self-compacting material modified with recycled steel fibers (RSF) from waste tires and spent equilibrium catalyst (Ecat) from the petrochemical industry for ultra-high performance application. For this purpose, 17 different mixtures were developed and analysed using different percentages of RSF (0%-3%) and replacement of cement by different percentages of Ecat (0%-15%). The developed mortars' self-compatibility was evaluated in a fresh stage using mini-cone tests. Regarding the hardened stage, the mortars were characterized at the ages of 7 days and 28 days using compression and unnotched flexural tests. The abilities of RSF to increase the post-cracking behavior of the specimens and to use Ecat to increase the bond performance between RSF and the cement matrix were assessed by performing notched three-point bending tests. The results of notched flexural tests were used to obtain the residual flexural strength in service limit state (SLS), ultimate limit state (ULS), and two equivalent flexural strengths. The experimental results for the fresh stage demonstrated that inclusion of RSF and Ecat significantly reduced the workability of mortars. The beneficial use of RSF and Ecat was observed to increase compressive strength and flexural strength for 7 days and 28 days of tested specimens. Notched flexural tested specimens showed that the addition of RSF and Ecat can significantly decrease the brittle behavior of cement-based materials by improving its toughness and post-cracking resistance. Middle-span deflection, crack initiation load, and ultimate flexural load were also increased with the addition of RSF and Ecat. In this sense, the results of this research showed that RSF and Ecat seem to have the potential to constitute a sustainable material for structural and nonstructural applications. Materials science ; Catalysis ; Composite material ; Chemistry ; Organic chemistry Advanced ceramic materials synthesis ; Epoxy Resin Curing Processes ; Innovative concrete reinforcement materials
Authors: Čačić Kenjerić, Frane
Source: University of Zagreb University Computing Centre (SRCE) (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

AI and Machine Vision in Food Processing As a global and vital part of modern life, the food process industry continues to evolve and develop, adopting newly developed tools and technologies to improve efficiency and ensure food safety while minimizing environmental impact and striving towards sustainability. Food processing is essential for preparing and preserving food for an ever-growing population. Artificial intelligence and machine vision technologies have emerged as promising tools in the food process industry, offering opportunities for enhanced quality control, increased productivity, and improved traceability. This article discusses the implementation of artificial intelligence and machine vision in the field of food process engineering, showcasing how these technologies can optimize processes, improve quality control, and contribute to sustainability in food production. Process (computing) ; Machine vision ; Food industry ; Food processing ; Quality (philosophy) ; Sustainability ; Field (mathematics) ; Food quality Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Listeria monocytogenes in Food Safety
Authors: Angelina Matuzko | Albina Fedorova | Л. А. Шарафутдинова
Source: NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY (article, 2023-04-24)
Field: Materials Science — Materials Chemistry

HISTOLOGICAL CHANGES IN THE ADRENAL GLANDS OF RATS AGAINST THE BACKGROUND OF SUBCHRONIC EXPOSURE TO TITANIUM DIOXIDE NANOPARTICLES Titanium dioxide ; Nanoparticle ; Biomedical engineering ; Chemistry ; Materials science ; Endocrinology ; Medicine ; Nanotechnology ; Metallurgy Nanoparticles: synthesis and applications ; Medical and Biological Ozone Research ; Spaceflight effects on biology
Authors: А. И. Алексеева | Sergey Drozd | Pavel V. Nikitin | Andrey Postnov | Aleksey Lipengolts | V. А. Skribitsky | Yulia Finogenova | Kseniya Shpakova | Aleksandr Khalansky | Igor Pronin | Galina Pavlova
Source: NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY (article, 2023-04-24)
Field: Materials Science — Biomaterials

COMPARATIVE MORPHOLOGICAL AND MOLECULAR GENETIC CHARACTERISTICS OF EXPERIMENTAL GLIOBLASTOMA 101/8 AND C6 Glioblastoma ; Computer science ; Computational biology ; Biology ; Cancer research Diatoms and Algae Research ; Bone and Dental Protein Studies ; Oral and Maxillofacial Pathology
Authors: Anna Samoylova | Alena Gostyuhina | Michael Bolshakov | V. M. Mochalova | Alexander Kalitin | К. В. Зайцев | О. П. Кутенков | В. В. Ростов
Source: NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY (article, 2023-04-24)
Field: Materials Science — Materials Chemistry

THE ROLE OF PARAMETERS OF NANOSECOND REPETITIVLY PULSED MICROWAVES IN PROLIFERATION OF RAT BONE MARROW STEM CELLS Nanosecond ; Bone marrow ; Stem cell ; Microwave ; Materials science ; Optoelectronics ; Biomedical engineering ; Cell biology ; Medicine ; Computer science ; Physics ; Biology ; Pathology ; Optics ; Telecommunications ; Laser Anodic Oxide Films and Nanostructures ; Advanced biosensing and bioanalysis techniques ; Silk-based biomaterials and applications
Authors: S. N. Myakisheva | Yulia Baburina | Roman Krestinin | Linda Sotnikova | Olga Krestinina
Source: NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY (article, 2023-04-24)
Field: Chemistry — Organic Chemistry

THE INFLUENCE OF DIETHYLDITHIOCARBAMATE ON PROLIFERATION OF MOUSE NEUROBLASTOMA CELLS N1E115 Neuroblastoma ; Cell growth ; Cancer research ; Cell biology ; Chemistry ; Biology ; Cell culture ; Biochemistry ; Genetics Chemical Synthesis and Reactions
Authors: Л. И. Матиенко | Elena Mil
Source: NEUROSCIENCE FOR MEDICINE AND PSYCHOLOGY (article, 2023-04-24)
Field: Chemistry — Inorganic Chemistry

AFM STUDY OF SYSTEMS SIMULATING THE ACTION OF NI(FE)ARD DIOXYGENASES AND CYTOCHROME P450-DEPENDENT MONOOXYGENASES Monooxygenase ; Atomic force microscopy ; Cytochrome P450 ; Action (physics) ; Chemistry ; Biological system ; Materials science ; Computer science ; Nanotechnology ; Physics ; Biology ; Enzyme ; Biochemistry Metal-Catalyzed Oxygenation Mechanisms ; Pharmacogenetics and Drug Metabolism ; Asymmetric Hydrogenation and Catalysis
Authors: Zhiqian Sun | Wangqing Li | Xiaolei Wang | Ning Li | Zhuang Qi | Shuo Weng
Source: The Canadian Journal of Chemical Engineering (article, 2023-05-24)
Field: Chemistry — Analytical Chemistry

Combined removal experiment of multiple impurities from W/O emulsions under high frequency pulsed electric field: Study on laws of desalination, decalcification, and deacidification Abstract Electrocoalescence is widely used to dehydrate crude oil, but impurities in crude oil are extremely complex, which greatly weaken the effect of dehydration. To understand the coupling law of various impurities, a static demulsification experiment was conducted under a high frequency and high voltage pulsed electric field to investigate the effects of electric field parameters (voltage, frequency, pulse width ratio), emulsification strength, electrocoalescence time, water content, acid value, injection alkali ratio, calcium content, decalcification agent concentration and removal process on desalination, decalcification, and deacidification. The results showed that the desalination and decalcification rates varied synchronously with the electric field parameters and water content. Additionally, the desalination and decalcification rates decreased with the emulsification strength, alkali injection ratio, acid value, and calcium content. Further, they increased first and then decreased with decalcifier concentration. The deacidification rate did not vary with the electric field parameters, but it strengthened with the water content and alkali injection ratio. Conversely, it decreased with the acid value, calcium content, and decalcifier concentration. Additionally, it increased first and then decreased with the emulsification intensity. The best removal procedure is deacidification followed by decalcification. These findings are helpful to achieve the combined removal of various impurities in crude oil. Bone decalcification ; Desalination ; Impurity ; Electric field ; Chemistry ; Materials science ; Alkali metal ; Chromatography ; Analytical Chemistry (journal) ; Organic chemistry Petroleum Processing and Analysis ; Electrohydrodynamics and Fluid Dynamics ; Enhanced Oil Recovery Techniques
Authors: Julian Arnold | Frank Schäfer | Alan Edelman | Christoph Bruder
Source: arXiv (Cornell University) (preprint, 2023-06-26)
Field: Materials Science — Materials Chemistry

Mapping out phase diagrams with generative classifiers One of the central tasks in many-body physics is the determination of phase diagrams. However, mapping out a phase diagram generally requires a great deal of human intuition and understanding. To automate this process, one can frame it as a classification task. Typically, classification problems are tackled using discriminative classifiers that explicitly model the probability of the labels for a given sample. Here we show that phase-classification problems are naturally suitable to be solved using generative classifiers based on probabilistic models of the measurement statistics underlying the physical system. Such a generative approach benefits from modeling concepts native to the realm of statistical and quantum physics, as well as recent advances in machine learning. This leads to a powerful framework for the autonomous determination of phase diagrams with little to no human supervision that we showcase in applications to classical equilibrium systems and quantum ground states. Generative grammar ; Discriminative model ; Computer science ; Probabilistic logic ; Artificial intelligence ; Intuition ; Machine learning ; Generative model Machine Learning in Materials Science ; Quantum many-body systems ; Protein Structure and Dynamics
Authors: Chien-Hsun Chen | Chih-Ju Chou
Source: Preprints.org (preprint, 2023-08-23)
Field: Materials Science — Materials Chemistry

Unveiling the Potential of Weak Partial Discharges: Enhancing Defect Recognition through Extended Measurement Duration and CNN-Based Analysis from PDIV to PDEV This study focuses on the impact of weak partial discharges (PDs) on defect recognition accuracy in epoxy resin through phase-resolved partial discharge (PRPD) analysis. Two measurement conditions are compared until PRPD pattern saturation: one-minute and one-hour durations. The PD data specifically target three void types located at different positions within the epoxy material. The aim is to evaluate how the presence of weak PDs at the PD extinction voltage (PDEV) influences defect recognition accuracy. This research sheds light on the potential implications of neglecting the significance of weak PD signals in defect detection. A convolutional neural network (CNN) model is trained using PRPD data recorded at the PD inception voltage (PDIV) and tested using the new PRPD data from both conditions recorded from a lower PDIV to a PDEV. The trained CNN model achieves a defect recognition accuracy of 100% for a one-hour duration, highlighting the importance of not neglecting weak PD signals. This emphasizes the significance of extended measurement duration and pattern saturation in capturing and analyzing weak PD signals for improved defect recognition. This study contributes to the advancement of practical applications by understanding the behavior of the epoxy material and enhancing defect detection techniques. Partial discharge ; Pattern recognition (psychology) ; Convolutional neural network ; Epoxy ; Voltage ; Artificial intelligence ; Materials science ; Void (composites) ; Duration (music) ; Saturation (graph theory) ; Biological system ; Computer science ; Acoustics ; Mathematics ; Physics ; Engineering ; Composite material ; Electrical engineering High voltage insulation and dielectric phenomena ; Industrial Vision Systems and Defect Detection ; Non-Destructive Testing Techniques
Authors: Lars Nieradzik | Jördis Sieburg-Rockel | Stephanie Helmling | Janis Keuper | Thomas Weibel | Andrea Olbrich | Henrike Stephani
Source: arXiv (Cornell University) (preprint, 2023-07-18)
Field: Chemistry — Organic Chemistry

Automating Wood Species Detection and Classification in Microscopic Images of Fibrous Materials with Deep Learning We have developed a methodology for the systematic generation of a large image dataset of macerated wood references, which we used to generate image data for nine hardwood genera. This is the basis for a substantial approach to automate, for the first time, the identification of hardwood species in microscopic images of fibrous materials by deep learning. Our methodology includes a flexible pipeline for easy annotation of vessel elements. We compare the performance of different neural network architectures and hyperparameters. Our proposed method performs similarly well to human experts. In the future, this will improve controls on global wood fiber product flows to protect forests. Pipeline (software) ; Hardwood ; Computer science ; Artificial intelligence ; Hyperparameter ; Identification (biology) ; Deep learning ; Artificial neural network ; Fiber ; Product (mathematics) ; Annotation ; Pattern recognition (psychology) ; Machine learning ; Materials science ; Biology ; Mathematics ; Ecology Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Industrial Vision Systems and Defect Detection
Authors: Yang Xu | Jing Zhang | Chuanxian Luo | Qinqing Huang | Hui Xu | Guozhi Zhang
Source: Energy Engineering (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Study on Intermittent Discharge Characteristics of Typical Solid Insulation Defects in Gas Insulated Switchgear In response to the problem of frequent leakage and false alarm of partial discharge insulation defects in GIS, this paper conducts experimental research on intermittent discharge characteristics of common solid insulation defects in GIS. Using true GIS to build a multi-source testing platform for intermittent discharge of solid insulation defects, and using pulse current method, ultra-high frequency method, ultrasonic method, and gas characteristic component detection method to study the variation law of intermittent discharge characteristics of solid insulation defects. The results show that: the intermittent discharge state of metal fouling defects on the solid insulation surface decreases with the extension of the discharge time, the discharge time interval as a whole shows an increasing trend, and the metal fouling defects on the solid insulation surface in the intermittent discharge state is difficult to develop into a breakdown discharge fault. The overall discharge amount of air gap defects inside solid insulation also shows the law of increasing first and then decreasing, and the discharge amount of air gap defects inside solid insulation stays at a large level for a long time during intermittent discharge, and there is a risk of breakdown, and the discharge will gradually evolve into continuous discharge; ultrasonic method and characteristic component detection method cannot realize the effective perception of intermittent discharge of metal fouling. The 50-period mapping information commonly used in the power field cannot reflect the intermittent discharge variation law of solid insulation, and the 200-period UHF mapping composed of four groups of 50-period UHF mapping data can initially derive the intermittent discharge distribution law of solid insulation defects. The research results of this paper are of great significance to expand the knowledge of intermittent discharge characteristics and the detection of GIS discharge defects in the field. Partial discharge ; Switchgear ; Materials science ; Insulation system ; Ultra high frequency ; Ultrasonic sensor ; Electrical engineering ; Forensic engineering ; Composite material ; Voltage ; Acoustics ; Engineering High voltage insulation and dielectric phenomena
Authors: Wenxi Zhang | Zhe Li | Weixi Li | Weisi Ma | Xinyi Chen | Si‐Zhe Li
Source: arXiv (Cornell University) (preprint, 2023-11-14)
Field: Materials Science — Materials Chemistry

Robust Learning Based Condition Diagnosis Method for Distribution Network Switchgear This paper introduces a robust, learning-based method for diagnosing the state of distribution network switchgear, which is crucial for maintaining the power quality for end users. Traditional diagnostic models often rely heavily on expert knowledge and lack robustness. To address this, our method incorporates an expanded feature vector that includes environmental data, temperature readings, switch position, motor operation, insulation conditions, and local discharge information. We tackle the issue of high dimensionality through feature mapping. The method introduces a decision radius to categorize unlabeled samples and updates the model parameters using a combination of supervised and unsupervised loss, along with a consistency regularization function. This approach ensures robust learning even with a limited number of labeled samples. Comparative analysis demonstrates that this method significantly outperforms existing models in both accuracy and robustness. Robustness (evolution) ; Computer science ; Switchgear ; Artificial intelligence ; Data mining ; Machine learning ; Curse of dimensionality ; Feature learning ; Unsupervised learning ; Categorization ; Outlier ; Engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Power System Reliability and Maintenance