jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jieyao Qin | Mingxi Lu | Bin Li | Xiaorui Li | Guangming You | Linjian Tan | Yikui Zhai | Meilin Huang | Yingzhu Wu
Source: Polymers (article, 2023-02-08)
Field: Materials Science — Polymers and Plastics

A Rapid Quantitative Analysis of Bicomponent Fibers Based on Cross-Sectional In-Situ Observation To accelerate the industrialization of bicomponent fibers, fiber-based flexible devices, and other technical fibers and to protect the property rights of inventors, it is necessary to develop fast, economical, and easy-to-test methods to provide some guidance for formulating relevant testing standards. A quantitative method based on cross-sectional in-situ observation and image processing was developed in this study. First, the cross-sections of the fibers were rapidly prepared by the non-embedding method. Then, transmission and reflection metallographic microscopes were used for in-situ observation and to capture the cross-section images of fibers. This in-situ observation allows for the rapid identification of the type and spatial distribution structure of the bicomponent fiber. Finally, the mass percentage content of each component was calculated rapidly by AI software according to its density, cross-section area, and total test samples of each component. By comparing the ultra-depth of field microscope, differential scanning calorimetry (DSC), and chemical dissolution method, the quantitative analysis was fast, accurate, economical, simple to operate, energy-saving, and environmentally friendly. This method will be widely used in the intelligent qualitative identification and quantitative analysis of bicomponent fibers, fiber-based flexible devices, and blended textiles. Materials science ; Microscope ; Fiber ; In situ ; Cross section (physics) ; Synthetic fiber ; Optical microscope ; Process engineering ; Computer science ; Composite material ; Optics ; Engineering ; Scanning electron microscope Textile materials and evaluations ; Advanced Sensor and Energy Harvesting Materials ; Industrial Vision Systems and Defect Detection
Authors: Md. Nazmul Al-Imran | S. W. Glass | Leonard S. Fifield | Mohammod Ali
Source: IEEE Sensors Journal (article, 2023-09-19)
Field: Materials Science — Materials Chemistry

A Reconfigurable Planar Capacitor Sensor for Thru the Jacket Dielectric Constant Measurement of Cable Insulation Planar capacitor sensors have been proposed to measure the aging-related dielectric constant variation of the jacket or insulation materials of cables. Although capacitor sensors have been used to monitor the aging of cable insulation by removing the jacket, through the jacket measurement of cable insulation dielectric constant variation is difficult because once the sensor is placed on the jacket it would either measure the aging of the jacket or that of the jacket and insulation together. A reconfigurable sensor along with innovative cable-specific models could be used to determine the jacket and insulation aging using the same sensor. For the proposed novel reconfigurable sensor, the electric field penetration depth is changed by activating and deactivating PIN diode switches. In one instance, the sensor measures the dielectric constant variation of the jacket, while in the next, it measures the dielectric constant variation of both the jacket and the insulation. By leveraging previously developed capacitance estimation models from large-scale finite element simulations for a specific cable, these two sets of measurement data are used to evaluate the aging-related dielectric constant variation of the insulation. Experimental data from aged cable specimens are presented to demonstrate the operation of the sensor. Dielectric ; Capacitor ; Capacitance ; Electrical engineering ; Materials science ; Electronic engineering ; Engineering ; Acoustics ; Voltage ; Physics ; Electrode High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Thermal Analysis in Power Transmission
Authors: Ye Tuo | Sawei Qiu | Erli Xia | Fang Luo | Wei Liu | Yuanzhi Wu
Source: Metals (article, 2023-08-13)
Field: Materials Science — Materials Chemistry

Mechanical Property and Microstructure of Rolled 7075 Alloy under Hot Compression with Different Original Grains The hot compression of rolled 7075 alloys with different heat treatments was performed. The temperature ranged from 200 to 400 °C, and the strain rate was 0.01 s−1. The stress level decreases with the increasing temperature during compression, and the strength of the alloy in the original condition is higher than that of solution-treated (ST) alloy at the same deformation condition. The alloys with different heat treatments exhibit different anisotropic behaviors at 200 °C; the anisotropy for the alloys in both conditions becomes weaker with increasing temperature. Then, the corresponding microstructure was studied. The alloy’s microstructure in its original condition consists of fiber grains; however, many equiaxed grains are found after solution treatment due to the recrystallization. The grains with different shapes lead to different anisotropic mechanical properties. For the alloys in both conditions, the density of the dislocation decreases with increasing temperature during compression, and a certain number of subgrains were found when deformed at 400 °C due to the higher driving force and a higher rate of atomic migration. Meanwhile, it is observed that the precipitates of the alloy become coarser during higher-temperature deformation. Dynamic softening is dominant in high-temperature deformation, decreasing stress during hot deformation. Materials science ; Microstructure ; Equiaxed crystals ; Alloy ; Softening ; Deformation (meteorology) ; Dynamic recrystallization ; Metallurgy ; Composite material ; Strain rate ; Compression (physics) ; Recrystallization (geology) ; Anisotropy ; Hot working Microstructure and mechanical properties ; Metallurgy and Material Forming ; Metal Alloys Wear and Properties
Authors: K. M. Satheesha | K. S. Rajanna | Krishna Prasad K
Source: International Journal of Applied Engineering and Management Letters (review, 2023-04-29)
Field: Chemistry — Analytical Chemistry

A Review of the Literature on Arecanut Sorting and Grading Using Computer Vision and Image Processing Background/Purpose: These days, the involvement of computer science in agriculture and food science is expanding. Classification and fault identification of diverse products employ a variety of Artificial Intelligence (AI), soft computing approaches, and methodologies, which contribute to higher-quality products for consumers. The position of Arecanuts in the international and Indian markets, as well as the application of computer vision and image processing to a system for categorizing and grading Arecanuts, are the main topics of this article. Objective: The development of a system for the automated categorization of Arecanut using images is limited by difficulties. To assess the value of computer vision application for Arecanut, it is critical to taken as account the traditional and economic significance of Arecanut. Design/Methodology/Approach: Several types of Arecanut are prone to great variation in color, texture, and form depending on the category and the area in which they are cultivated. Arecanuts are processed utilizing a variety of techniques, with an emphasis on the finished product's exterior. Here, the color, size, and texture of Arecanut are used to construct a classification or grading system. Findings/Result: With reference to the cited significant work that has been done on other fruits as well as Arecanuts from the standpoint of computer vision. This article provided a thorough introduction to Arecanuts, computer vision, and the uses and benefits of vision-aided technologies in the grading of Arecanuts and categorization. Result Limitations/Implications: This review is based on the detection and classification of the Arecanuts done using computer vision and AI techniques. Originality Value: Several inline resources including review papers on Arecanut, research articles, technical books, and website resources. Paper Type: Literature Review paper on smart auto Arecanut Sorting and Grading of Arecanut using Computer Vision and Image Processing Categorization ; Grading (engineering) ; Computer science ; Artificial intelligence ; Machine vision ; Soft computing ; Image processing ; Computer-aided ; Variety (cybernetics) ; Pattern recognition (psychology) ; Computer vision ; Engineering ; Artificial neural network ; Image (mathematics) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Coconut Research and Applications
Authors: abdallah elgharbawy
Source: Egyptian Journal of Chemistry (review, 2023-04-10)
Field: Materials Science — Polymers and Plastics

Expandable polystyrene production and market survey- A review Polystyrene is a hard, solid, and transparent polymer and it is a type of polyolefin used to make a wide variety of consumer products. There are different types of PS which are general-purpose polystyrene (GPPS) and expandable polystyrene (EPS). Polystyrene which has foam properties is called expanded polystyrene (EPS). EPS is a rigid, tough, white, and closed-cell foam that is made of pre-expanded PS beads. EPS is used for disposable trays, plates, bowls, cups, packaging applications, construction, and insulation applications. EPS beads are produced by two basic processes: the batch process and the impregnation method. In this paper, we are going to reveal the different production processes of PS and its global consumption and market. Production (economics) ; Polystyrene ; Business ; Economics ; Materials science ; Composite material ; Microeconomics Polymer Science and PVC ; Transport Systems and Technology ; BIM and Construction Integration
Authors: Juliane Glüge | Martin Scheringer
Source: Journal of Physical and Chemical Reference Data (article, 2023-10-13)
Field: Chemistry — Organic Chemistry

Evaluation of Physicochemical Property Data in the ECHA Database The database of the European Chemicals Agency (ECHA) is one of the most important databases that contains physicochemical properties, also because these data are used for the regulation of chemicals in the European Economic Area. The present study investigates the availability and quality of the data in the ECHA database for the logarithmic octanol–water partition coefficient (log10 KOW), solubility in water (SW), vapor pressure (pV), air–water partition coefficient, boiling point (Tb), second-order rate constant for the degradation with OH radicals, and the soil adsorption coefficient. For the evaluation of the data, calculations were run with COSMOtherm for the majority of the mono-constituent, neutral organic substances that are fully registered under the EU Regulation on the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH). The COSMOtherm data were evaluated against data from the PHYSPROP database, a manually curated database of experimental property data, to ensure that the COSMOtherm data were free of systematic errors. The comparison between COSMOtherm and the experimental data in the ECHA database showed that the data agree (within some variability) for many of the endpoints. However, there are also certain ranges with substantial discrepancies. These include log10 KOW &amp;gt; 8, SW &amp;lt; 10−3 mg/l, pV &amp;lt; 10−6 Pa, and Tb &amp;gt; 400 °C. The deviations between the non-experimental data and the COSMOtherm values are for all endpoints on average higher than the deviations between the experimental data and the COSMOtherm values. With this study, we provide COSMOtherm data for more than 4400 substances that can be used in the future for the hazard and risk assessment of these chemicals. Chemistry ; Database ; Partition coefficient ; Data quality ; Organic chemicals ; Thermodynamics ; Environmental chemistry ; Computer science ; Organic chemistry Chemical Thermodynamics and Molecular Structure ; Thermal and Kinetic Analysis ; Toxic Organic Pollutants Impact
Authors: Suma Arun Dev | Remya Unnikrishnan | P. S. Prathibha | K. Sijimol | V. B. Sreekumar | A AzharAli | E. V. Anoop | S. Viswanath
Source: 3 Biotech (article, 2023-05-12)
Field: Chemistry — Organic Chemistry

Artificial intelligence in timber forensics employing DNA barcode database Barcode ; Computer science ; Database ; DNA barcoding ; Computer security ; Biology ; Operating system Wood and Agarwood Research ; Image Processing and 3D Reconstruction ; Remote Sensing and LiDAR Applications
Authors: Giorgio Molteni | Alessandro Ponti
Source: ChemPhysChem (article, 2023-03-10)
Field: Chemistry — Organic Chemistry

Is DFT Accurate Enough to Calculate Regioselectivity? The Case of 1,3‐Dipolar Cycloaddition of Azide to Alkynes and Alkenes The importance of regioselectivity in 1,3-dipolar cycloadditions (DCs) makes it surprising that no benchmarking study on this problem has appeared. We investigated whether DFT calculations are an accurate tool to predict the regioselectivity of uncatalyzed thermal azide 1,3-DCs. We considered the reaction between HN<sub>3</sub> and 12 dipolarophiles, comprising ethynes HC≡C-R and ethenes H<sub>2</sub> C=CH-R (R=F, OH, NH<sub>2</sub> , Me, CN, CHO), which cover a broad range of electron demand and conjugation ability. We established benchmark data by the W3X protocol [complete-basis-set-extrapolated CCSD(T)-F12 energy with T-(T) and (Q) corrections and MP2-calculated core/valence and relativistic effects] and showed that core/valence effects and high-order excitations are important for accurate regioselectivity. Regioselectivities calculated using an extensive set of density functional approximations (DFAs) were compared with benchmark data. Range-separated and meta-GGA hybrids gave the best results. Good treatment of self-interaction and electron exchange are the key features for accurate regioselectivity. Dispersion correction slightly improves agreement with W3X results. The best DFAs provide the isomeric TS energy difference with an expected error ≈0.7 mh and errors ≈2 mh can occur. The isomer yield provided by the best DFA has an expected error of ±5 %, though errors up to 20 % are not rare. At present, an accuracy of 1-2 % is unfeasible but it seems that we are not far from achieving this goal. Regioselectivity ; Cycloaddition ; Chemistry ; Valence (chemistry) ; Density functional theory ; Computational chemistry ; Azide ; Organic chemistry ; Catalysis Organic Chemistry Cycloaddition Reactions ; Molecular Junctions and Nanostructures ; CO2 Reduction Techniques and Catalysts
Authors: Conor Cleeton | Felipe Lopes Oliveira | Rodrigo Neumann Barros Ferreira | Amir H. Farmahini | Binquan Luan | M. Steiner | Lev Sarkisov
Source: ChemRxiv (preprint, 2023-06-20)
Field: Chemistry — Inorganic Chemistry

A process-level perspective of the impact of molecular force fields on the computational screening of MOFs for carbon capture The question we pose in this study is to what extent the ranking of metal organic frameworks (MOFs) for adsorption-based carbon capture, and the selection of top performers identified in Pressure Swing Adsorption (PSA) process modelling, depends on the choice of the commonly available forcefields. To answer this question, we first generated distributions of CO2 and N2 adsorption isotherms via molecular simulation in 690 MOFs using six typical forcefields: the UFF or Dreiding sets of Lennard-Jones parameters, in combination with partial charges derived from ab initio calculations or by charge equilibration schemes. We then conducted a systematic uncertainty quantification study using PSA process-level modelling. We observe that: (i) the ranking of MOFs significantly depends on the choice of forcefield; (ii) partial charge assignment is the prevailing source of uncertainty, and that charge equilibration schemes produce results which are inconsistent with ab initio-derived charges; iii) the choice of Lennard-Jones parameters is a considerable source of uncertainty. Our work highlights that is not really possible to obtain material rankings with high resolution using a single molecular modelling approach and that, as a minimum, some uncertainty should be estimated for the performance of MOFs shortlisted using high throughput computational screening workflows. Future prospects for computational screening studies are also discussed. Ranking (information retrieval) ; Partial charge ; Molecular dynamics ; Ab initio ; Adsorption ; A priori and a posteriori ; Process (computing) ; Statistical physics ; Charge (physics) ; Work (physics) ; Chemistry ; Computer science ; Thermodynamics ; Computational chemistry ; Physics ; Physical chemistry ; Quantum mechanics ; Machine learning Metal-Organic Frameworks: Synthesis and Applications ; Phase Equilibria and Thermodynamics ; Carbon Dioxide Capture Technologies
Authors: Fayas Asharindavida | Omar Nibouche | James Uhomoibhi | Jun Liu | Jordan Vincent | Hui Wang
Source: Journal of Consumer Protection and Food Safety (article, 2023-05-19)
Field: Chemistry — Analytical Chemistry

Miniature spectrometer data analytics for food fraud Abstract Machine learning has been extensively used for analyzing spectral data in food quality management. However, collecting high-quality spectral data from miniature spectrometers outside the laboratory is challenging due to various factors such as distortions, noise, high dimensionality, and collinearity. This paper presents an in-depth analysis of food datasets collected from miniature spectrometers to evaluate the data quality and characteristics, by focusing on a case study of olive oil quality check, where various machine learning models were applied to differentiate pure and adulterated olive oil. Furthermore, the impact of pre-processing techniques on data distortions was studied. It presents a comprehensive pipeline, including data pre-processing, dimension reduction, classification, and regression analysis, and deploys different algorithms for comparative classification and regression analysis. The model performances were assessed using 2 separate methods: tenfold cross-validation on an entire dataset with 10% random testing, and an entire test set collected in different environments (multi-session validation). The first validation approach reached classification rates of up to 96.73%, while the second achieved 83.32%. These results demonstrate that cost-effective miniature spectrometers augmented with a suitable machine learning pipeline could execute classification tasks on par with non-portable and more expensive spectrometers. Furthermore, the study highlights the requirement of specialized algorithms to handle different ambient conditions affecting data acquisition and to eliminate performance gaps, making miniature spectrometers suitable for in situ scenarios. This work extends previous research to enable consumers becoming the first line in the defense against food fraud. Computer science ; Spectrometer ; Collinearity ; Pipeline (software) ; Data quality ; Data mining ; Dimensionality reduction ; Quality (philosophy) ; Curse of dimensionality ; Data processing ; Machine learning ; Artificial intelligence ; Engineering ; Statistics ; Database ; Mathematics ; Metric (unit) Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Identification and Quantification in Food
Authors: Marius R. Bittermann | Tatiana I. Morozova | Santiago F. Velandia | Elham Mirzahossein | Antoine Deblais | Sander Woutersen | Daniel Bonn
Source: Langmuir (article, 2023-03-15)
Field: Chemistry — Organic Chemistry

Surface-Mediated Molecular Transport of a Lipophilic Fluorescent Probe in Polydisperse Oil-in-Water Emulsions Emulsions often act as carriers for water-insoluble solutes that are delivered to a specific target. The molecular transport of solutes in emulsions can be facilitated by surfactants and is often limited by diffusion through the continuous phase. We here investigate this transport on a molecular scale by using a lipophilic molecular rotor as a proxy for solutes. Using fluorescence lifetime microscopy we track the transport of these molecules from the continuous phase toward the dispersed phase in polydisperse oil-in-water emulsions. We show that this transport comprises two time scales, which vary significantly with droplet size and surfactant concentration, and, depending on the type of surfactant used, can be limited either by transport across the oil–water interface or by diffusion through the continuous phase. By studying the time-resolved fluorescence of the fluorophore, accompanied by molecular dynamics simulations, we demonstrate how the rate of transport observed on a macroscopic scale can be explained in terms of the local environment that the probe molecules are exposed to. Fluorophore ; Pulmonary surfactant ; Chemistry ; Phase (matter) ; Fluorescence ; Molecular diffusion ; Diffusion ; Oil droplet ; Chemical physics ; Molecular dynamics ; Chemical engineering ; Molecule ; Water transport ; Emulsion ; Analytical Chemistry (journal) ; Chromatography ; Organic chemistry ; Thermodynamics ; Water flow ; Computational chemistry ; Optics Surfactants and Colloidal Systems ; Lipid Membrane Structure and Behavior ; Spectroscopy and Quantum Chemical Studies
Authors: Massimo Pica Ciamarra | Wencheng Ji | Matthieu Wyart
Source: arXiv (Cornell University) (preprint, 2023-02-10)
Field: Materials Science — Materials Chemistry

Local vs. Cooperative: Unraveling Glass Transition Mechanisms with SEER Which phenomenon slows down the dynamics in super-cooled liquids and turns them into glasses is a long-standing question of condensed-matter. Most popular theories posit that as the temperature decreases, many events must occur in a coordinated fashion on a growing length scale for relaxation to occur. Instead, other approaches consider that local barriers associated with the elementary rearrangement of a few particles or `excitations' govern the dynamics. To resolve this conundrum, our central result is to introduce an algorithm, SEER, which can systematically extract hundreds of excitations and their energy from any given configuration. We also provide a novel measurement of the activation energy, characterizing the liquid dynamics, based on fast quenching and reheating. We use these two methods in a popular liquid model of polydisperse particles. Such polydisperse models are known to capture the hallmarks of the glass transition and can be equilibrated efficiently up to millisecond time scales. The analysis reveals that cooperative effects do not control the fragility of such liquids: the change of energy of local barriers determines the change of activation energy. More generally, these methods can now be used to measure the degree of cooperativity of any liquid model. Millisecond ; Relaxation (psychology) ; Transition (genetics) ; Glass transition ; Materials science ; Chemical physics ; Physics ; Nuclear magnetic resonance ; Chemistry ; Psychology ; Polymer ; Astronomy ; Social psychology Material Dynamics and Properties