jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lea Fellner | Marian Kraus | Florian Gebert | Arne Walter | Frank Duschek
Source: Sensors (article, 2020-04-29)
Field: Chemistry — Spectroscopy

Multispectral LIF-Based Standoff Detection System for the Classification of CBE Hazards by Spectral and Temporal Features Laser-induced fluorescence (LIF) is a well-established technique for monitoring chemical processes and for the standoff detection of biological substances because of its simple technical implementation and high sensitivity. Frequently, standoff LIF spectra from large molecules and bio-agents are only slightly structured and a gain of deeper information, such as classification, let alone identification, might become challenging. Improving the LIF technology by recording spectral and additionally time-resolved fluorescence emission, a significant gain of information can be achieved. This work presents results from a LIF based detection system and an analysis of the influence of time-resolved data on the classification accuracy. A multi-wavelength sub-nanosecond laser source is used to acquire spectral and time-resolved data from a standoff distance of 3.5 m. The data set contains data from seven different bacterial species and six types of oil. Classification is performed with a decision tree algorithm separately for spectral data, time-resolved data and the combination of both. The first findings show a valuable contribution of time-resolved fluorescence data to the classification of the investigated chemical and biological agents to their species level. Temporal and spectral data have been proven as partly complementary. The classification accuracy is increased from 86% for spectral data only to more than 92%. Multispectral image ; Computer science ; Decision tree ; Data set ; Fluorescence ; Spectral bands ; Artificial intelligence ; Remote sensing ; Sensitivity (control systems) ; Pattern recognition (psychology) ; Biological system ; Optics ; Physics ; Engineering ; Electronic engineering ; Geology Spectroscopy and Laser Applications ; Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Toshiyuki Koyama | Munekazu Ohno | Akinori Yamanaka | Tadashi Kasuya | Susumu Tsukamoto
Source: MATERIALS TRANSACTIONS (article, 2020-07-16)
Field: Materials Science — Materials Chemistry

Development of Microstructure Simulation System in SIP-Materials Integration Projects A simulation system for the phase transformations and microstructure changes in welded area of steels was built with Materials Integration (MI) concepts. We aimed to build an simulation environment suitable not only for conducting research on microstructure developments and performing high-quality simulations but also for integrating practical and academic viewpoints and insights from materials science and engineering. In particular, the methods discussed in this article, such as the coordination of CCT diagrams and phase field (PF) simulations, and combination between PF methods and cellular automaton method, are typical examples of the MI concept. The detail of framework on the simulation system is explained, comprehensively. Microstructure ; Viewpoints ; Materials science ; Cellular automaton ; Welding ; Systems engineering ; Field (mathematics) ; Phase (matter) ; Computer science ; Mechanical engineering ; Metallurgy ; Engineering Solidification and crystal growth phenomena ; Aluminum Alloy Microstructure Properties ; Magnetic Properties and Applications
Authors: Shabana Urooj | Tanya Singh | Mohammad Amir | Mohd Tariq
Source: European Journal of Electrical Engineering and Computer Science (article, 2020-10-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optimal Design of Power Transformer with Advance Core Material using ANSYS Technique Due to indulge behavior of core materials and losses that leads to degradation of transformer efficiency. This research paper evaluating the optimal performance of transformer with designing of a newly core material namely as Mo.Me6. A possibility of increment in the efficiency for designed proposed model of transformer is observable. Also, a comparative analytical study based on the different designs of core type transformer with various core materials. The design and evaluation are performed on the Maxwell ANSYS electronic desktop platform, which provides an optimized design of transformer for practical applications. Whether it is a power transformer having lower frequency applications use in electronic circuits such as rectifying circuits or higher frequency applications power distribution circuit, etc. All transformer designs require performance evaluation in the working field and better efficiency to optimize the overall three-phase type core transformer. In this paper, proposed Mo.Me6 material with improved physical properties have been present of transformer efficiency and optimal design of core. The criteria include the changes in some effective parameters of the core, bringing out advancement in the working efficiency of the transformer. There is an opportunity to have a choice of desired material as designed particularly for the customer need making it will be more reliable and more suitable for various changeable conditions. For more efficient and effective working of transformer, this paper suggests core design with ANSYS techniques to achieve mentioned high efficiency with lower losses. Transformer ; Distribution transformer ; Energy efficient transformer ; Computer science ; Transformer types ; Electronic engineering ; Electronic circuit ; Electrical engineering ; Engineering ; Voltage Magnetic Properties and Applications ; Induction Heating and Inverter Technology ; Silicon Carbide Semiconductor Technologies
Authors: Lingjie Yang | Zuxin Zhang | Xiaowen Hu
Source: Sensors (article, 2020-11-18)
Field: Chemistry — Analytical Chemistry

Cultivar Discrimination of Single Alfalfa (Medicago sativa L.) Seed via Multispectral Imaging Combined with Multivariate Analysis Rapid and accurate discrimination of alfalfa cultivars is crucial for producers, consumers, and market regulators. However, the conventional routine of alfalfa cultivars discrimination is time-consuming and labor-intensive. In this study, the potential of a new method was evaluated that used multispectral imaging combined with object-wise multivariate image analysis to distinguish alfalfa cultivars with a single seed. Three multivariate analysis methods including principal component analysis (PCA), linear discrimination analysis (LDA), and support vector machines (SVM) were applied to distinguish seeds of 12 alfalfa cultivars based on their morphological and spectral traits. The results showed that the combination of morphological features and spectral data could provide an exceedingly concise process to classify alfalfa seeds of different cultivars with multivariate analysis, while it failed to make the classification with only seed morphological features. Seed classification accuracy of the testing sets was 91.53% for LDA, and 93.47% for SVM. Thus, multispectral imaging combined with multivariate analysis could provide a simple, robust and nondestructive method to distinguish alfalfa seed cultivars. Multispectral image ; Cultivar ; Principal component analysis ; Medicago sativa ; Multivariate statistics ; Support vector machine ; Multivariate analysis ; Artificial intelligence ; Pattern recognition (psychology) ; Agronomy ; Mathematics ; Biology ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: G. Polder | Aoife Gowen
Source: Journal of Spectral Imaging (article, 2020-02-27)
Field: Chemistry — Analytical Chemistry

The hype in spectral imaging Hyperspectral imaging is currently a very well-known and much used technology for measuring features in different fields, such as chemistry, geology, medicine, food and agriculture, either spaceborne (satellites), airborne (drones) or at close proximity (e.g. field scanning, industrial sorting lines or microscopy). Its background is two-fold, and it can be considered as a special case of spectroscopy (“imaging spectroscopy”) or a special case of imaging (“spectral imaging”). Current practice is to use adjectives such as multi and hyper added to “spectral imaging” in order to characterise the number of wavelength bands. In this paper we propose the community to use scientifically sound terminology, like “imaging spectroscopy” or “spectral imaging”, without using ambiguous adjectives. Further, we encourage the community to define and agree upon clear adjectives to describe the number of variables in the naming of our imaging technique. Hyperspectral imaging ; Imaging spectroscopy ; Spectral imaging ; Spectroscopy ; Terminology ; Imaging spectrometer ; Imaging science ; Chemical imaging ; Computer science ; Remote sensing ; Optics ; Artificial intelligence ; Physics ; Geology ; Spectrometer ; Linguistics ; Astronomy Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Advanced Chemical Sensor Technologies
Authors: Xinjun Hu | Ping Chen | Jianping Tian | Danping Huang | Huibo Luo | Dan Huang
Source: International Journal of Food Engineering (article, 2020-08-27)
Field: Chemistry — Analytical Chemistry

Predicting the moisture content of Daqu with hyperspectral imaging Abstract Daqu, a Chinese liquor fermentation starter, contains all kinds of microorganisms and enzymes for Chinese liquor fermentation. The moisture content of Daqu significantly influence on the reproduction of microorganisms in Daqu. This work presents for the first time that determination of moisture content of Daqu with hyperspectral imaging. The characteristic spectrum of water is extracted based on comparative experiments with varying moisture content. The molds based on the full bands and feature bands were established by the support vector regression (SVR) method, which is used to predict moisture content of Daqu during fermentation process. The performance of the model based on the feature bands ( R 2 = 0.9870, root mean square error (RMSE) = 0.0091) is comparable to the full bands and the dimensions of the spectral information were significantly reduced. This work presents a novel, rapid and nondestructive approach for detecting the moisture content in Daqu and lays a foundation for the application of hyperspectral imaging. Hyperspectral imaging ; Water content ; Moisture ; Mean squared error ; Fermentation ; Environmental science ; Remote sensing ; Mathematics ; Computer science ; Food science ; Artificial intelligence ; Materials science ; Chemistry ; Statistics ; Engineering ; Geography Spectroscopy and Chemometric Analyses ; Fermentation and Sensory Analysis ; Meat and Animal Product Quality
Authors: Roberto Peverati
Source: International Journal of Quantum Chemistry (article, 2020-07-09)
Field: Chemistry — Organic Chemistry

Fitting elephants in the density functionals zoo: Statistical criteria for the evaluation of density functional theory methods as a suitable replacement for counting parameters Abstract Counting parameters has become customary in the density functional theory community as a way to infer the transferability of popular approximations to the exchange‐correlation functionals. Recent work in data science, however, has demonstrated that the number of parameters of a fitted model is not related to the complexity of the model itself, nor to its eventual overfitting. Using similar arguments, here, we show that it is possible to represent every modern exchange‐correlation functional approximations using just one single parameter. This procedure proves the futility of the number of parameters as a measure of transferability. To counteract this shortcoming, we introduce and analyze the performance of three statistical criteria for the evaluation of the transferability of exchange‐correlation functionals. The three criteria are called Akaike information criterion, Vapnik‐Chervonenkis criterion, and cross‐validation criterion and are used in a preliminary assessment to rank 60 exchange‐correlation functional approximations using the ASCDB database of chemical data. Overfitting ; Akaike information criterion ; Correlation ; Transferability ; Measure (data warehouse) ; Computer science ; Rank (graph theory) ; Rank correlation ; Mathematics ; Data mining ; Machine learning ; Logit Chemical Thermodynamics and Molecular Structure ; Computational Drug Discovery Methods ; Free Radicals and Antioxidants
Authors: Rufo I. Marasigan
Source: International Journal of Emerging Trends in Engineering Research (article, 2020-02-15)
Field: Chemistry — Analytical Chemistry

Copra Meat Classification using Convolutional Neural Network Copra in the Philippines is one of the by-products from coconut which contributes as one of the major sources of income of Filipino farmers. During the process of selling the Copra in the market, farmers usually lose in the price competition from the buyers due to the unidentified quality of their Copra. Copra which commonly either overcooked or undercooked are paid as half of the price of the perfectly cooked. This happened due to the lack of information of the farmers in assessing the quality of the processed copra meat. In this study, a Convolutional Neural Network had been evaluated in terms of its accuracy by varying the numbers of convolutional layer filters, the size of filters, and its activation function. The identified best parameters were used to develop a CNN algorithm that classifies the quality of Copra. The algorithm was implemented using Tensorflow in a python environment. A series of tests were applied to the final CNN model. Random images of Copra with identified quality were used as testing data. Out of 120 sample images, the final CNN model performs an overall 86% accuracy. The model was also implemented into a simple android application for validation. The confusion matrix and f-score were used to evaluate the performance of the system. Copra ; Convolutional neural network ; Computer science ; Pattern recognition (psychology) ; Artificial intelligence ; Food science ; Biology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality
Authors: Karolina Śliwa | Paweł Śliwa
Source: Journal of Functional Biomaterials (article, 2020-08-07)
Field: Chemistry — Spectroscopy

The Accumulated Effect of the Number of Ethylene Oxide Units and/or Carbon Chain Length in Surfactants Structure on the Nano-Micellar Extraction of Flavonoids Classical extraction methods used for isolation of active substances from plant material are expensive, complicated and often environmentally unfriendly. The ultrasonic assistance micelle-mediated extraction method (UAMME), based on green chemistry principles, seems to be an interesting alternative. This work aimed to find a connection between the chemical structure of non-ionic surfactants and the efficiency of the extraction process. The effect of hydrophobic chain length and number of ethoxy groups on the quality of <i>Bidens tripartite</i> extracts was investigated. Several ethoxylated fatty alcohols were used: Ceteareth-20, Steareth-20, Oleth-20, Oleth-10, Oleth-5, C12-C13 Pareth-12, C12-C15 Pareth-12 and Ceteareth-12. The bioflavonoid compositions with the HPLC method was determined. The hydrophilic lipophilic balance (HLB) of studied surfactants, as well as the surface tension of surfactant solutions, were compared, to determine the explanation for the obtained differences in bioflavonoids concentration. The structural changes influenced by polyphenol extraction were monitored using Dynamic Light Scattering (DLS) measurements. In this work, probably for the first time, the connection between the chemical structure of non-ionic surfactants and the efficiency of the extraction process was found. The experimental and theoretical approach rationalized the choice of an appropriate eluent. We propose some structurally dependent factors, whose optimal value gave a high efficiency to the UAMME. Extraction (chemistry) ; Materials science ; Pulmonary surfactant ; Micelle ; Alkoxy group ; Surface tension ; Dynamic light scattering ; Polyphenol ; Alkyl ; Critical micelle concentration ; Ionic bonding ; Chemical engineering ; Ethylene oxide ; Chemical structure ; Chromatography ; Organic chemistry ; Chemistry ; Nanotechnology ; Nanoparticle ; Composite material ; Aqueous solution Analytical Chemistry and Chromatography ; Surfactants and Colloidal Systems ; Essential Oils and Antimicrobial Activity
Authors: Luqman Hakim Mohd Azmi | Daryl R. Williams | Bradley P. Ladewig
Source: Process Safety and Environmental Protection (article, 2020-04-01)
Field: Chemistry — Inorganic Chemistry

Can metal organic frameworks outperform adsorptive removal of harmful phenolic compound 2-chlorophenol by activated carbon? Adsorption ; Activated carbon ; Metal-organic framework ; Chemistry ; Aqueous solution ; Carbon fibers ; Chlorophenol ; Pollutant ; Nuclear chemistry ; Inorganic chemistry ; Materials science ; Organic chemistry ; Phenol Metal-Organic Frameworks: Synthesis and Applications ; Adsorption and biosorption for pollutant removal ; Covalent Organic Framework Applications
Authors: Bogusław Buszewski | Agnieszka Rogowska | Viorica Railean‐Plugaru | Michał Złoch | Justyna Walczak‐Skierska | Paweł Pomastowski
Source: Materials (article, 2020-05-23)
Field: Materials Science — Materials Chemistry

The Influence of Different Forms of Silver on Selected Pathogenic Bacteria The application of silver nanoparticles as an antibacterial agent is becoming more common. Unfortunately, their effect on microorganisms is still not fully understood. Therefore, this paper attempts to investigate the influence of silver ions, biologically synthesized silver nanoparticles and nanoparticles functionalized with antibiotics on molecular bacteria profiles. The initial stage of research was aimed at the mechanism determination involved in antibiotics sorption onto nanoparticles' surface. For this purpose, the kinetics study was performed. Next, the functionalized formulations were characterized by Fourier transform infrared spectroscopy (FT-IR), dynamic light scattering (DLS) and a zeta potential study. The results reveal that functionalization is a complex process, but does not significantly affect the stability of biocolloids. Furthermore, the antimicrobial assays, in most cases, have shown no increases in antibacterial activity after nanoparticle functionalization, which suggests that the functionalization process does not always generate the improved antimicrobial effect. Finally, the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) technique was employed to characterize the changes in the molecular profile of bacteria treated with various antibacterial agents. The recorded spectra proved many differences in bacterial lipids and proteins profiles compared to untreated cells. In addition, the statistical analysis of recorded spectra revealed the strain-dependent nature of stress factors on the molecular profile of microorganisms. Zeta potential ; Surface modification ; Silver nanoparticle ; Nanoparticle ; Antimicrobial ; Fourier transform infrared spectroscopy ; Desorption ; Dynamic light scattering ; Bacteria ; Chemistry ; Materials science ; Antibacterial activity ; Chemical engineering ; Nanotechnology ; Nuclear chemistry ; Combinatorial chemistry ; Organic chemistry ; Physical chemistry Nanoparticles: synthesis and applications ; Essential Oils and Antimicrobial Activity ; Bacterial biofilms and quorum sensing
Authors: Prakash Kumar Jha | Vinay Kumar Jha
Source: Mongolian Journal of Chemistry (article, 2020-12-31)
Field: Materials Science — Materials Chemistry

Iodine adsorption characteristics of activated carbon obtained from Spinacia Oleracea (spinach) leaves Spinach leaves powder was modified by activation with conc. H2SO4 and was characterized by using FTIR, optical microscopy, XRD analysis and methylene blue adsorption method. The maximum specific surface area measured by the Methylene blue adsorption method was 499 m2/g. The adsorption of iodine was investigated by varying parameters as pH, adsorbent dose, contact time and I2 concentration. The adsorption process was fitted to the Langmuir model controlled by pseudo - second – order kinetics with a constant rate value of 0.00305 g/(mg·min). The maximum adsorption was at pH 10. The maximum adsorption capacity was 909.091 mg/g. The ∆G value was -25 kJ/mole, which confirmed the physico - chemcal adsorption process. Adsorption ; Methylene blue ; Spinacia ; Spinach ; Chemistry ; Nuclear chemistry ; Activated carbon ; Iodine ; Iodine value ; Langmuir adsorption model ; Fourier transform infrared spectroscopy ; Kinetics ; Chromatography ; Analytical Chemistry (journal) ; Catalysis ; Chemical engineering ; Organic chemistry ; Biochemistry Covalent Organic Framework Applications
Authors: Gonzalo Angulo | Arnulf Rosspeintner
Source: The Journal of Chemical Physics (article, 2020-07-28)
Field: Chemistry — Physical and Theoretical Chemistry

Bimolecular photo-induced electron transfer enlightened by diffusion Photochemical electron transfer between freely diffusing molecules has been studied extensively. Here, we try to elucidate how much these works have contributed to the understanding of electron transfer. To this end, we have revisited the work performed in the experimental and theoretical areas of concern from the beginning of the 20th century up to the present day. We present a critical look at the major contributions and compile the current picture of a variety of phenomena around electron transfer in solution. This is based on two main developments, besides the theory of Marcus: encounter theories of diffusion and laser techniques in time-resolved spectroscopy. Electron transfer ; Diffusion ; Chemical physics ; Electron ; Variety (cybernetics) ; Spectroscopy ; Marcus theory ; Chemistry ; Physics ; Photochemistry ; Computer science ; Quantum mechanics ; Kinetics Photochemistry and Electron Transfer Studies ; Spectroscopy and Quantum Chemical Studies ; CO2 Reduction Techniques and Catalysts
Authors: Wei Cao | Mengqi Huang | Chao‐Hui Yeh | Kamyar Parto | Kaustav Banerjee
Source: IEEE Transactions on Electron Devices (article, 2020-02-26)
Field: Materials Science — Materials Chemistry

Impact of Transport Anisotropy on the Performance of van der Waals Materials-Based Electron Devices Layered van der Waals (vdW) semiconductors have emerged as preferred materials for building nextgeneration electronic devices, such as diodes and fieldeffect transistors (FETs), because of their capability of providing high mobility at the nanometer-scale thickness, as well as their flexibility and pristine interfaces. However, the inherent “vdW gaps” in these materials lead to much larger cross-plane resistivity, with respect to in-plane resistivity, thereby forming intriguing transport anisotropy. In this article, using extensive numerical simulations, it is found that this anisotropy introduces anomalous current transport behavior in vdW-based electron devices in which the current conducts in both the in-plane and cross-plane directions, including stacked heterojunction diodes and thin-film transistors (TFTs). Our study reveals for the first time that transport anisotropy degrades the performance of these devices, especially when devices are scaled (<; 0.6 μm) and/or relatively thicker materials (>4 nm) are used. Potential solutions to alleviate degradation are discussed as well. Materials science ; Anisotropy ; van der Waals force ; Diode ; Optoelectronics ; Transistor ; Semiconductor ; Heterojunction ; Electron mobility ; Electron ; Conductivity ; Electrical resistivity and conductivity ; Condensed matter physics ; Engineering physics ; Electrical engineering ; Optics ; Physics ; Engineering Graphene research and applications ; 2D Materials and Applications ; MXene and MAX Phase Materials