jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Timur Madzhidov | Arkadii Lin | Ramil Nugmanov | Natalia Dyubankova | Timur Gimadiev | Jörg K. Wegner | Assima Rakhimbekova | Tagir Akhmetshin | Zarina Ibragimova | Alexandre Varnek | Rail Suleymanov | Hugo Ceulemans | Jonas Verhoeven
Source: ChemRxiv (preprint, 2020-09-30)
Field: Materials Science — Materials Chemistry

Atom-to-Atom Mapping: A Benchmarking Study of Popular Mapping Algorithms and Consensus Strategies Here, we discuss a reaction standardization protocol followed by a comparison of popular Atom-to-atom mapping (AAM) tools (ChemAxon, Indigo, RDTool, NextMove and RXNMapper) as well as some consensus AAM strategies. For this purpose, a dataset of 1851 manually curated and mapped reactions was prepared (the Golden dataset) and used as a reference set. It has been found that RXNMapper possesses the highest accuracy, despite the fact that it has some clear disadvantages. Finally, RXNMapper was selected as the best tool, and it was applied to map the USPTO dataset. The standardization protocol used to prepare the data, as well as the data itself are available in the GitHub repository https://github.com/Laboratoire-de-Chemoinformatique.&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;br&gt; Standardization ; Benchmarking ; Protocol (science) ; Atom (system on chip) ; Computer science ; Set (abstract data type) ; Algorithm ; Data mining ; Information retrieval ; Programming language ; Medicine Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Carolina Fernanda Sengling Cebin Coppa | Bruna L. Gonçalves | Sarah Hwa In Lee | Valéria M.R. Nunes | Cintia B. Gonçalves | Christianne Elisabete da Costa Rodrigues | Carlos Augusto Fernandes de Oliveira
Source: Quality Assurance and Safety of Crops & Foods (article, 2020-10-31)
Field: Chemistry — Organic Chemistry

Extraction of oleuropein from olive leaves and applicability in foods Oleuropein is a phenolic compound found in all parts of the olive tree (Olea europaea L.), although at higher levels in the leaves. The health benefits associated with the consumption of oleuropein include the prevention of cardiac diseases, improvement in lipid metabolism, and decrease in obesity-related disturbs, among others. In addition, several studies have shown that oleuropein presents antimicrobial, antioxidant, and inflammatory properties. The scientific interest in the methods for the extraction of oleuropein from olive leaves has markedly increased in recent years, aiming to extend its application in foods, cosmetics, and drugs. In this review, the extraction procedures available in the literature are described according to their advantages and disadvantages that directly affect the extraction yield. The applicability of oleuropein in food products is also discussed. Oleuropein ; Olea ; Olive leaf ; Extraction (chemistry) ; Food science ; Chemistry ; Oleaceae ; Cosmetics ; Olive oil ; Traditional medicine ; Horticulture ; Biology ; Medicine ; Chromatography ; Organic chemistry Edible Oils Quality and Analysis ; Antioxidant Activity and Oxidative Stress ; Essential Oils and Antimicrobial Activity
Authors: Mahdieh Shahmardani | Napat Vajragupta | Alexander Hartmaier
Source: Materials (article, 2020-02-06)
Field: Materials Science — Materials Chemistry

Robust Optimization Scheme for Inverse Method for Crystal Plasticity Model Parametrization A bottom-up material modeling based on a nonlocal crystal plasticity model requires information of a large set of physical and phenomenological parameters. Because of the many material parameters, it is inherently difficult to determine the nonlocal crystal plasticity parameters. Therefore, a robust method is proposed to parameterize the nonlocal crystal plasticity model of a body-centered cubic (BCC) material by combining a nanoindentation test and inverse analysis. Nanoindentation tests returned the load-displacement curve and surface imprint of the considered sample. The inverse analysis is developed based on trust-region-reflective algorithm, which is the most robust optimization algorithm for the considered non-convex problem. The discrepancy function is defined to minimize both the load-displacement curves and the surface topologies of the considered material under applying varied indentation forces obtained from numerical models and experimental output. The numerical model results based on the identified material properties show good agreement with the experimental output. Finally, a sensitivity analysis performed changing the nonlocal crystal plasticity parameters in a predefined range emphasized that the geometrical factor has the most significant influence on the load-displacement curve and surface imprint parameters. Parametrization (atmospheric modeling) ; Scheme (mathematics) ; Crystal plasticity ; Inverse ; Plasticity ; Inverse problem ; Mathematical optimization ; Materials science ; Applied mathematics ; Biological system ; Mathematics ; Physics ; Mathematical analysis ; Composite material ; Geometry Nonlocal and gradient elasticity in micro/nano structures ; Composite Material Mechanics ; Numerical methods in engineering
Authors: Muhammad Adib Izzuddin
Source: Journal of Oil Palm Research (article, 2020-06-30)
Field: Chemistry — Analytical Chemistry

ANALYSIS OF MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLE (UAV) USING OBJECT-BASED IMAGE ANALYSIS FOR DETECTION OF Ganoderma DISEASE IN OIL PALM Ganoderma disease that affects oil palms has caused huge losses to the palm oil industry in Malaysia. Multispectral image ; Palm oil ; Remote sensing ; Aerial image ; Ganoderma ; Computer vision ; Artificial intelligence ; Aerial imagery ; Object detection ; Palm ; Environmental science ; Computer science ; Image (mathematics) ; Geography ; Biology ; Pattern recognition (psychology) ; Agroforestry ; Ganoderma lucidum ; Food science Spectroscopy and Chemometric Analyses
Authors: Gopalakrishnan Sai Gautam | Ellen B. Stechel | Emily A. Carter
Source: Advanced Theory and Simulations (article, 2020-08-17)
Field: Materials Science — Materials Chemistry

A First‐Principles‐Based Sub‐Lattice Formalism for Predicting Off‐Stoichiometry in Materials for Solar Thermochemical Applications: The Example of Ceria Abstract Theoretical models that reliably can predict off‐stoichiometry in materials via accurate descriptions of underlying thermodynamics are crucial for energy applications. For example, transition‐metal and rare‐earth oxides that can tolerate a large number of oxygen vacancies, such as CeO 2 and doped CeO 2 , can split water and carbon dioxide via a two‐step, oxide‐based solar thermochemical (STC) cycle. The search for new STC materials with a performance superior to that of state‐of‐the‐art CeO 2 can benefit from predictions accurately describing the thermodynamics of oxygen vacancies. The sub‐lattice formalism, a common tool used to fit experimental data and build temperature‐composition phase diagrams, can be useful in this context. Here, sub‐lattice models are derived solely from zero‐temperature quantum mechanics calculations to estimate fairly accurate temperature‐ and oxygen‐partial‐pressure‐dependent off‐stoichiometries in CeO 2 and Zr‐doped CeO 2 . Physical motivations for deriving some of the “excess” sub‐lattice model parameters directly from quantum mechanical calculations, instead of fitting to minimize deviations from experimental and/or theoretical data, are identified. Important limitations and approximations of the approach used are specified and extensions to multi‐cation oxides are also suggested to help identify novel candidates for water and carbon dioxide splitting and related applications. Stoichiometry ; Formalism (music) ; Thermodynamics ; Lattice (music) ; Materials science ; Oxide ; Statistical physics ; Thermochemistry ; Phase transition ; Oxygen ; Chemistry ; Physics ; Physical chemistry ; Quantum mechanics Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Chemical Looping and Thermochemical Processes
Authors: Aurora J. Cruz‐Cabeza | Eleanor Taylor | Isaac J. Sugden | David Bowskill | S. E. Wright | H. Abdullahi | D. Tulegenov | G. Sadiq | Roger J. Davey
Source: CrystEngComm (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Can solvated intermediates inform us about nucleation pathways? The case of β-<i>p</i>ABA Using crystallography to search for nucleation pathways: α and β polymorphs of <italic>p</italic>-aminobenzoic acid. Nucleation ; Chemistry ; Chemical physics ; Computational chemistry ; Organic chemistry Crystallization and Solubility Studies ; Crystallography and molecular interactions ; Enzyme Structure and Function
Authors: Vjačeslavs Lapkovskis | Viktors Mironovs | Андрей Викторович Касперович | Vadim Myadelets | Dmitri Goljandin
Source: Preprints.org (review, 2020-09-14)
Field: Materials Science — Biomaterials

Crumb Rubber as a Secondary Raw Material from Waste Rubber: A Short Review of Processing Methods Despite the development of technologies, modern methods of disposal of end-of-life tires most often represent either the incineration in cement kilns or the destruction of tires in special landfills, showing a lack of sustainable recycling of this valuable material. The fundamental role of recycling is evident, and the development of high-efficiency processes represents a priority for the European market. Therefore, investigation of end-of-life rubber processing methods is of high importance for manufacturers and recyclers of rubber materials. In this paper, methods of processing of end-of-life tires are reviewed in order to obtain rubber crumb, which can later be used in the production of new industrial rubber goods and composite The processes of separation end-of-life tire into fractions by type of materials using mechanical processing methods along with mechanochemical and mechanical processes of processing the materials of used tires in order to obtain crumb rubber of various fractions and chemical reactivity are considered. Crumb rubber ; Natural rubber ; Kiln ; Raw material ; Waste management ; Incineration ; Production (economics) ; Environmental science ; Materials science ; Engineering ; Composite material biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Polymer Nanocomposites and Properties
Authors: Sergei V. Kalinin | Maxim Ziatdinov | Rama K. Vasudevan
Source: Journal of Applied Physics (article, 2020-07-08)
Field: Materials Science — Materials Chemistry

Guided search for desired functional responses via Bayesian optimization of generative model: Hysteresis loop shape engineering in ferroelectrics Advances in theoretical modeling across multiple disciplines have yielded generative models capable of high veracity in predicting macroscopic functional responses of materials emerging as a result of complex non-local interactions. Correspondingly, of interest is the inverse problem of finding the model parameter that will yield desired macroscopic responses, such as stress–strain curves, ferroelectric hysteresis loops, etc. Here, we suggest and implement Gaussian process based methods that allow to effectively sample the degenerate parameter space of a complex non-local model to output regions of parameter space which yield desired functionalities. We discuss the specific adaptation of the acquisition function and sampling function to make the process efficient and balance the efficient exploration of parameter space for multiple possible minima and exploitation to densely sample the regions of interest where target behaviors are optimized. This approach is illustrated via the hysteresis loop engineering in ferroelectric materials but can be adapted to other functionalities and generative models. Maxima and minima ; Computer science ; Parameter space ; Generative model ; Gaussian process ; Hysteresis ; Process (computing) ; Function (biology) ; Bayesian optimization ; Algorithm ; Statistical physics ; Gaussian ; Artificial intelligence ; Biological system ; Generative grammar ; Mathematics ; Physics ; Statistics ; Mathematical analysis Machine Learning in Materials Science ; Ferroelectric and Piezoelectric Materials ; Piezoelectric Actuators and Control
Authors: Yuqian Gao | Thomas Fillmore | Nathalie Munoz Munoz | Gayle J. Bentley | Christopher W. Johnson | Joonhoon Kim | Jamie A. Meadows | Jeremy Zucker | Meagan Burnet | Anna K. Lipton | Aivett Bilbao Pena | Danny Orton | Young‐Mo Kim | Ronald Moore | Errol Robinson | Scott Baker | Bobbie‐Jo Webb‐Robertson | Adam M. Guss | John M. Gladden | Gregg T. Beckham | Jon Magnuson | Kristin Burnum-Johnson
Source: Frontiers in Bioengineering and Biotechnology (article, 2020-12-02)
Field: Chemistry — Spectroscopy

High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440 Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in <i>Pseudomonas putida</i> KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM. Pseudomonas putida ; Mass spectrometry ; Chromatography ; Proteomics ; Sensitivity (control systems) ; Liquid chromatography–mass spectrometry ; Quantitative proteomics ; Chemistry ; Selected reaction monitoring ; Tandem mass spectrometry ; Enzyme ; Biochemistry ; Engineering Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Genomics and Phylogenetic Studies
Authors: Michał Rogala
Source: Advances in Science and Technology – Research Journal (article, 2020-08-05)
Field: Materials Science — Materials Chemistry

Neural Networks in Crashworthiness Analysis of Thin-Walled Profile with Foam Filling This article presents the numerical tests of thin-walled compressed columns with a square cross-section. The crush efficiency indicators were determined using the finite element method (Abaqus) and neural networks of MLP. The models had a constant circular trigger, with a diameter of 32 mm. During dynamic analysis, the samples were loaded with 1700 J. The numerical models were filled with aluminum foam from 40 mm to 180 mm every 20 mm. The study presents the conclusions for the thin-walled models with crushable foam. Crashworthiness ; Materials science ; Artificial neural network ; Metal foam ; Composite material ; Vehicle safety ; Structural engineering ; Automotive engineering ; Computer science ; Finite element method ; Engineering ; Artificial intelligence ; Aluminium High-Velocity Impact and Material Behavior
Authors: Wei Sun | Hiroya Ohta | Taku Ninomiya | Yasunori Goto
Source: Journal of Micro/Nanolithography MEMS and MOEMS (article, 2020-05-12)
Field: Materials Science — Surfaces, Coatings and Films

High-voltage CD-SEM-based application to monitor 3D profile of high-aspect-ratio features Background: In-line metrology for three-dimensional (3D) profiling high-aspect-ratio (HAR) features is highly important for manufacturing semiconductor devices, particularly for memory devices, such as 3D NAND and DRAM. Aim: Our purpose was to obtain the cross-sectional profiles of the HAR features from top-view critical dimension scanning electron microscopy (CD-SEM) images. Approach: Based on Monte Carlo simulation results, we proposed a method for 3D profiling of HAR features using backscattered electron (BSE) signal intensities. Several kinds of HAR holes with different taper angles and bowing geometries were fabricated. High-voltage CD-SEM was used for experiments to determine the feasibility of our approach. Results: Using the BSE line-profile, we constructed cross sections of the taper holes and estimated sidewall angles (SWAs), which were approximately the same as those observed using field-emission scanning electron microscopy (FE-SEM). The constructed cross sections of the bowing holes and the trends of the geometric variance, which were estimated by the middle CD and its depth, were consistent with the cross sections observed by FE-SEM. Conclusions: The results demonstrate that the variation in the HAR holes, such as SWA and bowing geometry, can be measured and monitored using the BSE images. Bowing ; Scanning electron microscope ; Materials science ; Critical dimension ; Dram ; Aspect ratio (aeronautics) ; Profiling (computer programming) ; Metrology ; Optics ; Optoelectronics ; Physics ; Composite material ; Computer science Electron and X-Ray Spectroscopy Techniques ; Advancements in Photolithography Techniques ; Advanced Electron Microscopy Techniques and Applications
Authors: Mohammad Al Ktash | Otto Hauler | Edwin Ostertag | Marc Brecht
Source: Journal of Spectral Imaging (article, 2020-12-16)
Field: Chemistry — Analytical Chemistry

Ultraviolet-visible/near infrared spectroscopy and hyperspectral imaging to study the different types of raw cotton Different types of raw cotton were investigated by a commercial ultraviolet-visible/near infrared (UV-Vis/NIR) spectrometer (210–2200 nm) as well as on a home-built setup for NIR hyperspectral imaging (NIR-HSI) in the range 1100–2200 nm. UV-Vis/NIR reflection spectroscopy reveals the dominant role proteins, hydrocarbons and hydroxyl groups play in the structure of cotton. NIR-HSI shows a similar result. Experimentally obtained data in combination with principal component analysis (PCA) provides a general differentiation of different cotton types. For UV-Vis/NIR spectroscopy, the first two principal components (PC) represent 82 % and 78 % of the total data variance for the UV-Vis and NIR regions, respectively. Whereas, for NIR-HSI, due to the large amount of data acquired, two methodologies for data processing were applied in low and high lateral resolution. In the first method, the average of the spectra from one sample was calculated and in the second method the spectra of each pixel were used. Both methods are able to explain ≥90 % of total variance by the first two PCs. The results show that it is possible to distinguish between different cotton types based on a few selected wavelength ranges. The combination of HSI and multivariate data analysis has a strong potential in industrial applications due to its short acquisition time and low-cost development. This study opens a novel possibility for a further development of this technique towards real large-scale processes. Hyperspectral imaging ; Principal component analysis ; Near-infrared spectroscopy ; Ultraviolet ; Spectroscopy ; Spectrometer ; Ultraviolet visible spectroscopy ; Materials science ; Analytical Chemistry (journal) ; Remote sensing ; Optics ; Chemistry ; Optoelectronics ; Computer science ; Artificial intelligence ; Physics ; Chromatography ; Geology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Ning Liu | Gang Liu | Hong Sun
Source: Sensors (article, 2020-06-17)
Field: Chemistry — Analytical Chemistry

Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System In this study, a SPAD value detection system was developed based on a 25-wavelength spectral sensor to give a real-time indication of the nutrition distribution of potato plants in the field. Two major advantages of the detection system include the automatic segmentation of spectral images and the real-time detection of SPAD value, a recommended indicating parameter of chlorophyll content. The modified difference vegetation index (MDVI) linking the Otsu algorithm (OTSU) and the connected domain-labeling (CDL) method (MDVI-OTSU-CDL) is proposed to accurately extract the potato plant. Additionally, the segmentation accuracy under different modified coefficients of MDVI was analyzed. Then, the reflectance of potato plants was extracted by the segmented mask images. The partial least squares (PLS) regression was employed to establish the SPAD value detection model based on sensitive variables selected using the uninformative variable elimination (UVE) algorithm. Based on the segmented spectral image and the UVE-PLS model, the visualization distribution map of SPAD value was drawn by pseudo-color processing technology. Finally, the testing dataset was employed to measure the stability and practicality of the developed detection system. This study provides a powerful support for the real-time detection of SPAD value and the distribution of crops in the field. Artificial intelligence ; Otsu's method ; Pattern recognition (psychology) ; Partial least squares regression ; Segmentation ; Computer science ; Mathematics ; Field (mathematics) ; Image segmentation ; Statistics Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Water Quality Monitoring and Analysis