jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Momen Kamal Tageldeen | Ilias Pagkalos | Sara S. Ghoreishizadeh | Emmanuel M. Drakakis
Source: Biosensors and Bioelectronics (article, 2023-03-03)
Field: Chemistry — Electrochemistry

Analogue circuit realisation of surface-confined redox reaction kinetics The literature on voltammetry and electrochemical impedance spectroscopy (EIS) recognises the importance of using large-amplitude sinusoidal perturbations to better characterise electrochemical systems. To identify the parameters of a given reaction, various electrochemical models with different sets of values are simulated and compared against the experimental data to determine the best-fit set of parameters. However, the process of solving these nonlinear models is computationally expensive. This paper proposes analogue circuit elements for synthesising surface-confined electrochemical kinetics at the electrode interface. The resultant analogue model could be used as a solver to compute reaction parameters as well as a tracker for ideal biosensor behaviour. The performance of the analogue model was verified against numerical solutions to theoretical and experimental electrochemical models. Results show that the proposed analogue model has a high accuracy of at least 97% and a wide bandwidth of up to 2 kHz. The circuit consumed an average power of 9 μW. Electrochemistry ; Equivalent circuit ; Dielectric spectroscopy ; Electrical impedance ; Solver ; Analyte ; Cyclic voltammetry ; Biological system ; Nonlinear system ; Redox ; Electrode ; Materials science ; Chemistry ; Analytical Chemistry (journal) ; Computer science ; Voltage ; Physics ; Physical chemistry ; Inorganic chemistry Electrochemical Analysis and Applications ; Conducting polymers and applications ; Electrochemical sensors and biosensors
Authors: Tahir Ölmez
Source: OALib (article, 2023-01-01)
Field: Materials Science — Biomaterials

What Is the Relationship between the Faraday’s Constant Numbers and Silk Worms as Regards to Quantum Perspective Model? This paper attempts to express the Faraday's constant numbers with chemical nucleotide bases (A T, G, C and U) as regards to Quantum Perspective Model. At first, the exact value of the Faraday's constant numbers after the comma is lined up in doublets (0, 96 48 53 32 12 33 10 01 84 10 5 Cmol -1 ). Secondly, convert this twin decimal base numbers to binary number base system. Thirdly, after converting process of these numbers, convert this binary numbers as decimal number base system again. Fourthly, sum this decimal base numbers respectively. Fifthly, total sum of the adding processes corresponds to genetic codes [Adenine (A), Thymine (T), Guanine (G), Cytosine (C) and Uracil (U)]. Sixthly, approximately the consequence of this conversion corresponds to Uracil (U) and Guanine (G) nucleotide bases. Namely, the number "64" equals to Uracil (U) nucleotide base and proximate the number "79" equals to Guanine (G) nucleotide base. Seventhly, after converting [Uracil (U) and Guanine (G)] nucleotide bases to ["AG" Adenine (A) and Guanine (G)], this result is significant not only with the link between the Faraday's constant numbers in Electrochemistry, but also the link between dual positions of Superposition in Quantum Physics. Eighthly, after searching ["AG" Adenine (A) and Guanine (G)] sequences in the NCBI (The National Center for Biotechnology Information) database, the NCBI search result was similar to silk worm (Bombyx Mori) gene sequence "AGAAAAAGGA". They are very interesting specific model organisms for the genetics of silkworms with this sequence and the possibility of genetic engineering for the Silk Cocoon Membrane (SCM). Ninthly, this complex natural protein fibrous membrane is of great interest in the research community due to its possibility of having good electrical conductivity properties. Finally, this article revealed not only the relationship between Faraday's constant How to cite this paper: SILK ; Perspective (graphical) ; Constant (computer programming) ; Faraday cage ; Quantum ; Theoretical physics ; Physics ; Quantum mechanics ; Mathematics ; Computer science ; Telecommunications ; Magnetic field ; Geometry Silk-based biomaterials and applications
Authors: Fathur Rohman | Dani Mardiyana | Fabrobi Fazlur Ridha | Satish Kumar Damodar
Source: INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) (article, 2023-05-30)
Field: Materials Science — Materials Chemistry

STRUCTURAL ANALYSIS OF WASTE SEPARATION MACHINE FRAME USING FEA METHOD Waste has become a significant problem that requires significant management. Automatic waste separator machine technology has been developed by many countries to help with waste management efficiency. The working principle of the automatic waste separator is to separate the types of organic and non-organic waste. In making the machine frame, this must be taken into account carefully. Here the Autodesk Inventor 2021 application is used to analyze the strength of the frame of an automatic garbage separator. In the frame strength analysis simulation, the type of material used is ASTM A36 Steel with a U-shaped iron plate profile with a thickness of 6 mm. The total load on the frame is 284.5 kg. The static simulation results show that the maximum von misses stress is 138.285 MPa with a maximum displacement of 16.28 mm. while the value of safety factor is 1.4 ul. Based on the results of the simulation analysis, the value of the safety factor is included in the value range (1.25 -2.0) and the value of von misses ≤ 200 MPa (Modulus of elasticity) for ASTM A36 material, which means that the frame design for the waste separator machine meets good safety standards. Separator (oil production) ; Finite element method ; Structural engineering ; Lead frame ; Frame (networking) ; Static analysis ; Waste material ; Engineering ; Waste management ; Mechanical engineering ; Materials science ; Composite material Material Selection and Properties
Authors: Stefan Meinecke | Felix Köster | Dominik Christiansen | Kathy Lüdge | Andreas Knorr | Malte Selig
Source: Physical review. B./Physical review. B (article, 2023-05-11)
Field: Materials Science — Materials Chemistry

Data-driven forecasting of nonequilibrium solid-state dynamics We present a data-driven approach to efficiently approximate nonlinear transient dynamics in solid-state systems. Our proposed machine-learning model combines a dimensionality reduction stage with a nonlinear vector autoregression scheme. We report an outstanding time-series forecasting performance combined with an easy-to-deploy model and an inexpensive training routine. Our results are of great relevance as they have the potential to massively accelerate multiphysics simulation software and thereby guide the future development of solid-state-based technologies. Massively parallel ; Multiphysics ; Computer science ; Nonlinear system ; Dimensionality reduction ; Curse of dimensionality ; Relevance (law) ; Software ; Transient (computer programming) ; Time series ; Reduction (mathematics) ; Statistical physics ; Machine learning ; Physics ; Parallel computing Machine Learning in Materials Science ; Theoretical and Computational Physics ; Neural Networks and Applications
Authors: Junze Huang | Binyang Xu
Source: Applied and Computational Engineering (article, 2023-06-14)
Field: Materials Science — Materials Chemistry

Diffusion-limited aggregation Models of physical processes from the fields of physics and chemistry may be used to create a variety of beautiful visuals and structures that resemble living things. Diffusion limited aggregation, also known as DLA, is an illustration of this. It is a term used to explain, among other things, how zinc ions diffuse and assemble onto electrodes in an electrolytic solution. "Diffusion" refers to the random movement of the particles that make up the structure before they adhere ("Aggregate") to it. "Diffusion-limited" refers to the fact that the structure grows one particle at a time rather than in chunks of particles because the particles are thought to be in low concentrations, preventing them from coming into touch with one another. Other instances include the development of coral, the route of lightning, the coalescence of dust or smoke particles, and the development of certain crystals.Nature uses a variety of interesting and often simple processes to produce amazing shapes, patterns, and forms that span all scales and never cease to surprise and enlighten the keen observer. From the From the micro to the macro, matter uses a variety of logical, observable processes to arrange, enhance, and transform, often stacking on top of each other in complex ways. In this paper, Mathematicians will discuss a process called diffusion-restricted aggregation or DLA, which uses randomly moving and "sticky" particles to produce fractal branching structures. Diffusion-limited aggregation ; Variety (cybernetics) ; Coalescence (physics) ; Chemical physics ; Statistical physics ; Nanotechnology ; Fractal ; Computer science ; Physics ; Materials science ; Mathematics ; Artificial intelligence ; Fractal dimension Pickering emulsions and particle stabilization ; Electrostatics and Colloid Interactions ; Theoretical and Computational Physics
Authors: M. Herrera | Jesús Hernández‐Saz | Natalia Fernández‐Delgado | Luisa M. Valencia | Sergio I. Molina
Source: Polymer Testing (article, 2023-09-30)
Field: Materials Science — Surfaces, Coatings and Films

Low dose electron tomography of novel nanocomposites for additive manufacturing The development of new nanocomposites with added functionalities for Additive Manufacturing (AM) requires of a deep understanding of the 3D distribution of the selected nano-additives within the polymeric matrix, in order to optimize their performance. For this, electron tomography (ET) is an outstanding analysis technique that requires the material to withstand the electron exposure needed for the acquisition of several tens of images, becoming challenging for beam-sensitive materials. In this work, we analyse the parameters involved in the successful analysis by low dose ET of nanocomposites based in acrylic resins for stereolithography (SLA). Needle-shape electron-transparent specimens have been fabricated by focused ion beam (FIB), minimizing surface damage due to the high energy Ga+ ions. Microscope settings for tuning the electron dose applied during the ET analysis of these nanoneedles are discussed. A phenomenological study of the effect of increasing the electron dose in the scanning transmission electron microscopy (STEM) analysis of the material has been carried out, showing that ET can be effectively performed at low electron doses. Two case studies are presented, to illustrate the relevance of these analyses in the development of nanocomposites with added functionalities. Our results have revealed the crucial role of the dose rate and of inaccuracies in the calculation of critical electron doses for the design of ET experiments. Materials science ; Electron tomography ; Nanocomposite ; Stereolithography ; Scanning electron microscope ; Transmission electron microscopy ; Focused ion beam ; Cathode ray ; Electron ; Electron beam-induced deposition ; Nanotechnology ; Secondary electrons ; Scanning transmission electron microscopy ; Biomedical engineering ; Composite material ; Ion ; Chemistry Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Ion-surface interactions and analysis
Authors: Steven A. Jacobs | Jeremy Kirch | Yaowei Hu | Suraj Suri | B. Knipfer | Z. Yu | D. Botez | Robert A. Marsland | L. J. Mawst
Source: APL Machine Learning (article, 2023-10-20)
Field: Chemistry — Spectroscopy

Optimization of a quantum cascade laser cavity for single-spatial-mode operation via machine learning Neural networks, trained with the ADAM algorithm followed by a globally convergent modification to Newton’s method, are developed to predict the threshold gain of the fundamental and first higher-order modes as functions of the refractive-index profile in a quantum cascade laser cavity. The networks are used to optimize the design of a refractive-index profile that provides essentially single-spatial-mode performance in a nominally multi-moded cavity by maximizing the threshold-gain differential between the modes. The use of neural networks allows the optimization to be performed in seconds, instead of days or weeks which would be required if Maxwell’s equations were repeatedly solved to obtain the threshold gains. Cascade ; Artificial neural network ; Quantum cascade laser ; Mode (computer interface) ; Laser ; Quantum ; Optics ; Refractive index ; Computer science ; Physics ; Control theory (sociology) ; Quantum mechanics ; Artificial intelligence ; Engineering Spectroscopy and Laser Applications ; Semiconductor Lasers and Optical Devices ; Photonic and Optical Devices
Authors: Povilas Kavaliauskas | Birutė Grybaitė | Rita Vaickelionienė | Birutė Sapijanskaitė-Banevič | Kazimieras Anusevičius | Agnė Kriaučiūnaitė | Gabrielė Smailienė | Vidmantas Petraitis | Rūta Petraitienė | Ethan Naing | Andrew Garcia | Vytautas Mickevičius
Source: Antibiotics (article, 2023-01-20)
Field: Chemistry — Organic Chemistry

Synthesis and Development of N-2,5-Dimethylphenylthioureido Acid Derivatives as Scaffolds for New Antimicrobial Candidates Targeting Multidrug-Resistant Gram-Positive Pathogens The growing antimicrobial resistance to last-line antimicrobials among Gram-positive pathogens remains a major healthcare emergency worldwide. Therefore, the search for new small molecules targeting multidrug-resistant pathogens remains of great importance. In this paper, we report the synthesis and in vitro antimicrobial activity characterisation of novel thiazole derivatives using representative Gram-negative and Gram-positive strains, including tedizolid/linezolid-resistant <i>S. aureus,</i> as well as emerging fungal pathogens. The 4-substituted thiazoles <b>3h</b>, and <b>3j</b> with naphthoquinone-fused thiazole derivative <b>7</b> with excellent activity against methicillin and tedizolid/linezolid-resistant <i>S. aureus</i>. Moreover, compounds <b>3h</b>, <b>3j</b> and <b>7</b> showed favourable activity against vancomycin-resistant <i>E. faecium</i>. Compounds <b>9f</b> and <b>14f</b> showed broad-spectrum antifungal activity against drug-resistant <i>Candida</i> strains, while ester <b>8f</b> showed good activity against <i>Candida auris</i> which was greater than fluconazole. Collectively, these data demonstrate that <i>N</i>-2,5-dimethylphenylthioureido acid derivatives could be further explored as novel scaffolds for the development of antimicrobial candidates targeting Gram-positive bacteria and drug-resistant pathogenic fungi. Antimicrobial ; Linezolid ; Multiple drug resistance ; Microbiology ; Fluconazole ; Antibiotic resistance ; Thiazole ; Staphylococcus aureus ; Antibiotics ; Chemistry ; Biology ; Bacteria ; Vancomycin ; Antifungal ; Stereochemistry Synthesis and biological activity ; Synthesis and Biological Evaluation ; Phenothiazines and Benzothiazines Synthesis and Activities
Authors: Muhammad Ishfaq Hussain | Muhammad Aasim Rafique | Wan‐Gil Jung | Bong‐Joong Kim | Moongu Jeon
Source: ACS Omega (article, 2023-05-12)
Field: Materials Science — Surfaces, Coatings and Films

Segmentation and Morphology Computation of a Spiky Nanoparticle Using the Hourglass Neural Network Morphological measurements of nanoparticles in electron microscopy images are tedious, laborious, and often succumb to human errors. Deep learning methods in artificial intelligence (AI) paved the way for automated image understanding. This work proposes a deep neural network (DNN) for the automated segmentation of a Au spiky nanoparticle (SNP) in electron microscopic images, and the network is trained with a spike-focused loss function. The segmented images are used for the growth measurement of the Au SNP. The auxiliary loss function captures the spikes of the nanoparticle, which prioritizes the detection of spikes in the border regions. The growth of the particles measured by the proposed DNN is as good as the measurement in manually segmented images of the particles. The proposed DNN composition with the training methodology meticulously segments the particle and consequently provides accurate morphological analysis. Furthermore, the proposed network is tested on an embedded system for integration with the microscope hardware for real-time morphological analysis. Artificial neural network ; Artificial intelligence ; Segmentation ; Computer science ; Computation ; Deep learning ; Nanoparticle ; Pattern recognition (psychology) ; Image segmentation ; Hourglass ; Electron microscope ; Biological system ; Computer vision ; Materials science ; Nanotechnology ; Algorithm ; Physics ; Optics ; Biology Electron and X-Ray Spectroscopy Techniques ; Cell Image Analysis Techniques ; Machine Learning in Materials Science
Authors: Sizenando Bispo-Silva | Cleverson J.F. Oliveira | Gabriel de Alemar Barberes
Source: Geosciences (article, 2023-10-24)
Field: Chemistry — Analytical Chemistry

Geochemical Biodegraded Oil Classification Using a Machine Learning Approach Chromatographic oil analysis is an important step for the identification of biodegraded petroleum via peak visualization and interpretation of phenomena that explain the oil geochemistry. However, analyses of chromatogram components by geochemists are comparative, visual, and consequently slow. This article aims to improve the chromatogram analysis process performed during geochemical interpretation by proposing the use of Convolutional Neural Networks (CNN), which are deep learning techniques widely used by big tech companies. Two hundred and twenty-one chromatographic oil images from different worldwide basins (Brazil, the USA, Portugal, Angola, and Venezuela) were used. The open-source software Orange Data Mining was used to process images by CNN. The CNN algorithm extracts, pixel by pixel, recurring features from the images through convolutional operations. Subsequently, the recurring features are grouped into common feature groups. The training result obtained an accuracy (CA) of 96.7% and an area under the ROC (Receiver Operating Characteristic) curve (AUC) of 99.7%. In turn, the test result obtained a 97.6% CA and a 99.7% AUC. This work suggests that the processing of petroleum chromatographic images through CNN can become a new tool for the study of petroleum geochemistry since the chromatograms can be loaded, read, grouped, and classified more efficiently and quickly than the evaluations applied in classical methods. Convolutional neural network ; Artificial intelligence ; Computer science ; Petroleum ; Pixel ; Pattern recognition (psychology) ; Visualization ; Process (computing) ; Deep learning ; Geology ; Machine learning Spectroscopy and Chemometric Analyses ; Geochemistry and Geologic Mapping ; Mineral Processing and Grinding
Authors: Raúl Colorado‐Peralta | Sonia A. Sánchez-Ruíz | Angelina Flores‐Parra
Source: Organics (article, 2023-06-15)
Field: Chemistry — Organic Chemistry

Structural and Dynamic Behaviour of Heterocycles Derived from Ethylenediamines with Formaldehyde: 1,3,5-Triazinanes and Bis(imidazolidinyl)methanes Formaldehyde is a simple chemical compound that is used as a building block in obtaining a wide range of products. The versatility of formaldehyde in chemical synthesis becomes evident when it is reacted with N-alkylethylenediamines. Therefore, this paper reports the structure and reactivity of a series of compounds derived from easily accessible molecules, such as formaldehyde, sodium hydrosulphide, and N-alkylethylenediamines. The 1,3,5-triazines (1a-1d) and bis(3-alkyl-imidazolidin-1-yl)methanes (2a-2d) were obtained by simple reaction conditions. Additionally, different proportions of sodium hydrosulphide and formaldehyde were used with N-benzylamine to obtain N-benzyltriazinane (3), N-benzylthiadiazinane (4) and N-benzyldithiazinane (5). All these compounds were characterized by analytical, spectroscopic, and spectrometric techniques, such as melting point, solubility, one-dimensional and two-dimensional nuclear magnetic resonance (13C, 1H, 15N, COSY, HETCOR, NOESY, COLOC), elemental analysis, high- and low-resolution mass spectrometry, among others. The structures of compounds 4 and 5 were obtained by single-crystal X-ray diffraction. The results show that small variations in the stoichiometry and the reaction conditions significantly influence the products obtained. Formaldehyde ; Chemistry ; Benzylamine ; Alkyl ; Stoichiometry ; Melting point ; Molecule ; Solubility ; Reactivity (psychology) ; Single crystal ; Elemental analysis ; Chemical shift ; Organic chemistry ; Analytical Chemistry (journal) ; Physical chemistry ; Crystallography Synthesis and Characterization of Heterocyclic Compounds ; Synthesis of heterocyclic compounds ; Structural and Chemical Analysis of Organic and Inorganic Compounds
Authors: Teruhisa Horita
Source: ECS Transactions (article, 2023-05-19)
Field: Materials Science — Materials Chemistry

Progress of the Evaluation and Analysis Methods for Durability of SOFC Stacks Recent progress in the development of R&amp;D for the evaluation and analytical methods of SOFC stack durability is reported under the NEDO Japanese national project. The goal of this project is the following two points: (1) to develop the advanced evaluation and analytical methods for the cell stacks which show a lifetime over 15 years (130 kh) with high efficiency of over 65% LHV, and (2) to develop the evaluation and analytical methods for dynamic operation mode such as rapid start-stop and load cycling. Three practical stacks (one flat tube and two types of planar) were supplied by the stack developers and tested over 10,000 hours with high fuel utilization (Uf~85%). It was found that the same evaluation methods can be applied to the stack resistance component determination between normal Uf (=75%) and high Uf (85%) conditions. Relatively stable performances were reported for these stacks and degradation factors were considered taking into account the degradation mechanisms at cells and stacks. Under high Uf conditions, some specific degradation mechanisms are now analyzed in the cells. For rapid starts of stacks, evaluation protocols are considered taking into account the mechanical stress arising from the thermal distribution in the cells. Simulation methods are considered for the evaluation of performance after 15 years of operation in the stacks. Stack (abstract data type) ; Durability ; Degradation (telecommunications) ; Computer science ; Process engineering ; Stress (linguistics) ; Temperature cycling ; Reliability engineering ; Nuclear engineering ; Materials science ; Mechanical engineering ; Thermal ; Engineering ; Composite material ; Physics Advancements in Solid Oxide Fuel Cells ; Fuel Cells and Related Materials ; Corrosion Behavior and Inhibition