jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fan Wu | Qingliang Yu | H.J.H. Brouwers
Source: Construction and Building Materials (article, 2022-02-04)
Field: Materials Science — Polymers and Plastics

Long-term performance of bio-based miscanthus mortar The long-term degradation behavior of embedded natural fibres is one of the key factors restricting the durability of bio-based mortars and concretes. In this study, to minimize the negative impact of miscanthus fibre on the service life of bio-based miscanthus mortar, the effects of different treatments (heat treatment, milling) on the long-term performance of bio-based miscanthus mortar are investigated. Results show that the heat-treated miscanthus fibres improve the compressive strength and flexural strength of miscanthus mortar by 82.7% and 26.9%, respectively, compared to the reference fibre, thanks to the reduced porosity and enhanced compatibility. The mechanical strength degradation of miscanthus mortar mainly occurs in the first month after being soaked in water. Moreover, the alkaline environment in miscanthus mortar causes the dissolution of some cellulosic components, resulting in the degradation of the miscanthus fibre. The removal of sugar from the miscanthus fibre is conducive to the strength development and durability of bio-based miscanthus mortar. It is concluded that heat-treated miscanthus fibres can be applied to improve the dimensional stability and degradation resistance of miscanthus mortar for better application of miscanthus in sustainable building materials. Miscanthus ; Mortar ; Durability ; Materials science ; Degradation (telecommunications) ; Raw material ; Pulp and paper industry ; Composite material ; Environmental science ; Waste management ; Biofuel ; Chemistry ; Bioenergy ; Engineering Natural Fiber Reinforced Composites ; Innovations in Concrete and Construction Materials ; Advanced Cellulose Research Studies
Authors: Virginie Lacotte | Sergio Peignier | M. Raynal | Isabelle Demeaux | François Delmotte | Pedro da Silva
Source: International Journal of Molecular Sciences (article, 2022-09-02)
Field: Chemistry — Analytical Chemistry

Spatial–Spectral Analysis of Hyperspectral Images Reveals Early Detection of Downy Mildew on Grapevine Leaves Downy mildew is a highly destructive disease of grapevine. Currently, monitoring for its symptoms is time-consuming and requires specialist staff. Therefore, an automated non-destructive method to detect the pathogen before the visible symptoms appear would be beneficial for early targeted treatments. The aim of this study was to detect the disease early in a controlled environment, and to monitor the disease severity evolution in time and space. We used a hyperspectral image database following the development from 0 to 9 days post inoculation (dpi) of three strains of <i>Plasmopara viticola</i> inoculated on grapevine leaves and developed an automatic detection tool based on a Support Vector Machine (SVM) classifier. The SVM obtained promising validation average accuracy scores of 0.96, a test accuracy score of 0.99, and it did not output false positives on the control leaves and detected downy mildew at 2 dpi, 2 days before the clear onset of visual symptoms at 4 dpi. Moreover, the disease area detected over time was higher than that when visually assessed, providing a better evaluation of disease severity. To our knowledge, this is the first study using hyperspectral imaging to automatically detect and show the spatial distribution of downy mildew on grapevine leaves early over time. Downy mildew ; Plasmopara viticola ; Hyperspectral imaging ; False positive paradox ; Support vector machine ; Artificial intelligence ; Biology ; Pattern recognition (psychology) ; Computer science ; Horticulture Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Remote Sensing in Agriculture
Authors: Yating Hu | Zhi Wang | Xiaofeng Li | Lei Li | Xigang Wang | Yanlin Wei
Source: Sensors (article, 2022-08-13)
Field: Chemistry — Analytical Chemistry

Nondestructive Classification of Maize Moldy Seeds by Hyperspectral Imaging and Optimal Machine Learning Algorithms Mildew of maize seeds may affect their germination rates and reduce crop quality. It is crucial to classify maize seeds efficiently and without destroying their original structure. This study aimed to establish hyperspectral datasets using hyperspectral imaging (HSI) of maize seeds with different degrees of mildew and then classify them using spectral characteristics and machine learning algorithms. Initially, the images were processed with Otus and morphological operations. Each seed's spectral features were extracted based on its coding, its edge, region of interest (ROI), and original pixel coding. Random forest (RF) models were optimized using the sparrow search algorithm (SSA), which is incapable of escaping the local optimum; hence, it was optimized using a modified reverse sparrow search algorithm (JYSSA) strategy. This reverse strategy selects the top 10% as the elite group, allowing us to escape from local optima while simultaneously expanding the range of the sparrow search algorithm's optimal solution. Finally, the JYSSA-RF algorithm was applied to the validation set, with 96% classification accuracy, 100% precision, and a 93% recall rate. This study provides novel ideas for future nondestructive detection of seeds and moldy seed selection by combining hyperspectral imaging and JYSSA algorithms based on optimized RF. Hyperspectral imaging ; Artificial intelligence ; Algorithm ; Sparrow ; Red edge ; Random forest ; Support vector machine ; Computer science ; Coding (social sciences) ; Pattern recognition (psychology) ; Mathematics ; Machine learning ; Biology ; Statistics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Tanmay Sarkar | Molla Salauddin | Kohima Kirtonia | Siddhartha Pati | Максим Ребезов | Mars Khayrullin | Svetlana Panasenko | Lyudmila Tretyak | Marina Temerbayeva | Nadezhda Kapustina | Sanаvar Azimova | Lyudmila M. Gruzdeva | Farrukh Makhmudov | И.А. Никитин | Amirzhan Kassenov | Mohammad Ali Shariati | José M. Lorenzo
Source: Applied Sciences (review, 2022-02-15)
Field: Chemistry — Analytical Chemistry

A Review on the Commonly Used Methods for Analysis of Physical Properties of Food Materials The chemical composition of any food material can be analyzed well by employing various analytical techniques. The physical properties of food are no less important than chemical composition as results obtained from authentic measurement data are able to provide detailed information about the food. Several techniques have been used for years for this purpose but most of them are destructive in nature. The aim of this present study is to identify the emerging techniques that have been used by different researchers for the analysis of the physical characteristics of food. It is highly recommended to practice novel methods as these are non-destructive, extremely sophisticated, and provide results closer to true quantitative values. The physical properties are classified into different groups based on their characteristics. The concise view of conventional techniques mostly used to analyze food material are documented in this work. Computer science ; Data science Spectroscopy and Chemometric Analyses ; Sensory Analysis and Statistical Methods ; Meat and Animal Product Quality
Authors: Giuseppe Bonifazi | Riccardo Gasbarrone | Roberta Palmieri | Silvia Serranti
Source: Sustainability (article, 2022-08-18)
Field: Chemistry — Analytical Chemistry

End-of-Life Textile Recognition in a Circular Economy Perspective: A Methodological Approach Based on Near Infrared Spectroscopy The life cycle of textiles (i.e., fabrics and apparel products) generates many environmental impacts, such as resource consumption, water, soil, and air pollution through the dispersion of chemical substances and greenhouse gases. For these reasons, in 2019, textiles were identified as a “priority product category for the circular economy” by the European Commission that proposed a new circular economy action plan focusing on recycling. An in-depth characterization of textile fabrics could lead to an ad hoc recycling procedure, reducing resource consumption and chemicals utilization. In this work, NIR (1000–1650 nm) spectroscopy was applied to extract information regarding fabric composition, with reference to cotton, silk, viscose, and some of their blends, using two different devices: a hyperspectral imaging (HSI) platform and a portable spectroradiometer. The different fabrics were correctly classified based on their spectral features by both detection instruments. The proposed methodological approach can be applied for quality control in the textile recycling sector at industrial and/or laboratory scale thanks to the easiness of use and the speed of detection. Circular economy ; Textile ; Life-cycle assessment ; Hyperspectral imaging ; Environmental science ; Resource (disambiguation) ; Process engineering ; Environmental economics ; Computer science ; Engineering ; Materials science ; Artificial intelligence ; Production (economics) ; Composite material Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Cultural Heritage Materials Analysis
Authors: Mu Ku Chen | Cheng Hung Chu | Xiaoyuan Liu | Jingcheng Zhang | Linshan Sun | Jin Yao | Yubin Fan | Yao Liang | Takeshi Yamaguchi | Takuo Tanaka | Din Ping Tsai
Source: IEEE Access (article, 2022-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Meta-Lens in the Sky Meta-lenses are advanced optical devices composed of artificial nano-antenna arrays. Its flat, light-weight, ultra-thin, compact, customizable, and easy-to-integrate advantages enable widely potential usages in new demands. We demonstrate a GaN-based polarization-independent meta-lens-based camera on a drone. The diameter of the meta-lens is 2.6 mm, and the measured focal length is 5.03 mm under the 532 nm light incident. An array of the 750 nm height cylindrical nano-antennas with various sizes of the meta-lens provides the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\pi $ </tex-math></inline-formula> phase modulation of the focusing phase distribution. The meta-lens is integrated with an image sensor and mounted on the drone to realize the aerial photography and landing assistance. By taking images of the specific pattern on the ground at different heights through the meta-lens, the flying height of the drone can be detected for landing and flying. We trust meta-lens-camera can reduce the weight burden for prolonging flight time. We believe the meta-lens-based optical devices for imaging and sensing is an important key for micro/nano-robots, micro air vehicles, and intelligent sensing devices in the future. Drone ; Lens (geology) ; Focal length ; Computer science ; Optics ; Artificial intelligence ; Camera module ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Claudia Pérez-Roncal | Silvia Arazuri Garín | Carlos López-Molina | Carmen Jarén | L.G. Santesteban | Ainara López-Maestresalas
Source: Computers and Electronics in Agriculture (article, 2022-03-14)
Field: Chemistry — Analytical Chemistry

Exploring the potential of hyperspectral imaging to detect Esca disease complex in asymptomatic grapevine leaves Precise and reliable identification of specific plant diseases is a challenge within precision agriculture nowadays. This is the case of esca, a complex grapevine trunk disease, that represents a major threat to modern viticulture as it is responsible for large economic losses annually. The lack of effective control strategies and the complexity of esca disease expression make essential the identification of affected plants, before symptoms become evident, for a better management of the vineyard. This study evaluated the suitability of a near-infrared hyperspectral imaging (HSI) system to detect esca disease in asymptomatic grapevine leaves of Tempranillo red-berried cultivar. For this, 72 leaves from an experimental vineyard, naturally infected with esca, were collected and scanned with a lab-scale HSI system in the 900-1700 nm spectral range. Then, effective image processing and multivariate analysis techniques were merged to develop pixel-based classification models for the distinction of healthy, asymptomatic and symptomatic leaves. Automatic and interval partial least squares variable selection methods were tested to identify the most relevant wavelengths for the detection of esca-affected vines using partial least squares discriminant analysis and different pre-processing techniques. Three-class and two-class classifiers were carried out to differentiate healthy, asymptomatic and symptomatic leaf pixels, and healthy from asymptomatic pixels, respectively. Both variable selection methods performed similarly, achieving good classification rates in the range of 82.77-97.17% in validation datasets for either three-class or two-class classifiers. The latter results demonstrated the capability of hyperspectral imaging to distinguish two groups of seemingly identical leaves (healthy and asymptomatic). These findings would ease the annual monitoring of disease incidence in the vineyard and, therefore, better crop management and decision making. Hyperspectral imaging ; Vineyard ; Asymptomatic ; Pixel ; Artificial intelligence ; Pattern recognition (psychology) ; Partial least squares regression ; Linear discriminant analysis ; Computer science ; Mathematics ; Biology ; Horticulture ; Machine learning ; Medicine ; Pathology Spectroscopy and Chemometric Analyses ; Plant Pathogens and Fungal Diseases ; Remote Sensing in Agriculture
Authors: Marzia Sara Vaccaro | Hamid M. Sedighi
Source: Engineering With Computers (article, 2022-07-13)
Field: Materials Science — Materials Chemistry

Two-phase elastic axisymmetric nanoplates Abstract In the present work, the two-phase integral theory of elasticity developed in Barretta et al. (Phys E 97:13–30, 2018) for nano-beams is generalized to model two-dimensional nano-continua. Notably, a well-posed mixture local/stress-driven nonlocal elasticity is proposed to accurately predict size effects in Kirchhoff axisymmetric nanoplates. The key idea is to express the elastic radial curvature as a convex combination of local and nonlocal integral responses, that is a coherent choice motivated by virtue of the plate axisymmetry. The relevant structural problem is shown to be governed by a set of integro-differential equations, whose solution is computationally onerous. Thus, Helmholtz’s averaging kernel is advantageously adopted, since it enables explicit inversion of the integral constitutive law by virtue of an equivalence property. Specifically, the elastostatic problem of axisymmetry nanoplates is equivalently formulated in a differential form whose solution in terms of transverse displacement field is governed by nonlocal and mixture parameters. A parametric study is performed for case studies of applicative interest, and numerical solutions are finally provided and discussed. The presented methodology can be adopted to design and optimization of plate-based nano-electro-mechanical-systems (NEMS). Helmholtz free energy ; Mathematics ; Curvature ; Mathematical analysis ; Differentiable function ; Elasticity (physics) ; Stress field ; Applied mathematics ; Classical mechanics ; Physics ; Geometry ; Finite element method Nonlocal and gradient elasticity in micro/nano structures ; Numerical methods in engineering ; Composite Structure Analysis and Optimization
Authors: Hua Hou | Yue Pan | Guoning Bai | Yuexin Li | Vignesh Murugadoss | Yuhong Zhao
Source: Advanced Composites and Hybrid Materials (article, 2022-04-11)
Field: Materials Science — Materials Chemistry

High-throughput computing for hydrogen transport properties in ε-ZrH2 Tetragonal crystal system ; Hydrogen ; Materials science ; Diffusion ; Density functional theory ; Thermodynamics ; Activation energy ; Phase (matter) ; Condensed matter physics ; Chemistry ; Physical chemistry ; Computational chemistry ; Physics Nuclear Materials and Properties ; Fusion materials and technologies ; Intermetallics and Advanced Alloy Properties
Authors: Marwa A. El‐Ghobashy | H. Hashim | Moustafa A. Darwish | Mayeen Uddin Khandaker | Abdelmoneim Sulieman | Nissren Tamam | Sergei Trukhanov | А.В. Труханов | Mohamed A. Salem
Source: Nanomaterials (article, 2022-03-27)
Field: Chemistry — Organic Chemistry

Eco-Friendly NiO/Polydopamine Nanocomposite for Efficient Removal of Dyes from Wastewater The rapid development of industries discharges huge amounts of wastewater that contain surface water. For this reason, we used NiO/polydopamine (NiO/PDA) nanocomposite as an efficient material for the removal of Methyl violet 2B from water. It was synthesized and then characterized by Fourier Transform Infrared (FT-IR) spectroscopy, X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray (EDX) analysis, Transmission Electron Microscopy (TEM), and Brunauer-Emmett-Teller (BET). The EDX analysis confirmed the presence of O, Ni, N, and C. The composite has an average particle size of 18 nm. Its surface area is 110.591 m<sup>2</sup>/g. It was found that the efficiency of dye removal by adsorption on NiO/PDA exceeded that of bare NiO. The adsorption capacity of NiO and NiO/PDA are 126 and 284 mg/g, respectively. The effects of adsorbent dose, dye concentration, and pH on the removal efficiency were examined. The efficiency increased with increasing the adsorbent dose and pH, but dropped from 85 to 73% within 30 min as the initial dye concentration was increased from 0.984 to 4.92 mg/L. Such a drop in the removal efficiency is due to the blocking of the surface-active sites of NiO/PDA, with the high population of dye molecules derived from the continuous increase in dye concentration. The adsorption results of the dye fitted well with the pseudo-second-order kinetics and Langmuir isotherm. The reusability data showed that NiO/PDA was stable across three adsorption-regeneration cycles, thus it can be considered a good recyclable and efficient adsorbent. Because of these results, it can be considered that this method can be applied for the treatment of wastewater. Non-blocking I/O ; Adsorption ; Materials science ; Nanocomposite ; Langmuir adsorption model ; Chemical engineering ; Fourier transform infrared spectroscopy ; Scanning electron microscope ; Wastewater ; Nuclear chemistry ; Langmuir ; Transmission electron microscopy ; Particle size ; BET theory ; Nanotechnology ; Chemistry ; Environmental engineering ; Composite material ; Organic chemistry ; Catalysis Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal ; Advanced Photocatalysis Techniques
Authors: Camille Gillet | Ferhat Tamssaouet | Bouchra Hassoune‐Rhabbour | Tatiana Tchalla | Valérie Nassiet
Source: Polymers (review, 2022-07-12)
Field: Materials Science — Polymers and Plastics

Parameters Influencing Moisture Diffusion in Epoxy-Based Materials during Hygrothermal Ageing—A Review by Statistical Analysis The hygrothermal ageing of epoxy resins and epoxy matrix composite materials has been studied many times in the literature. Models have been developed to represent the diffusion behaviour of the materials. For reversible diffusions, Fick, Dual–Fick and Carter and Kibler models are widely used. Many parameters, correlated or not, have been identified. The objectives of this review by statistical analysis are to confirm or infirm these correlations, to highlight other correlations if they exist, and to establish which are the most important to study. This study focuses on the parameters of the Fick, Dual–Fick and Carter and Kibler models. For this purpose, statistical analyses are performed on data extracted and calculated from individuals described in the literature. Box plot and PCA analyses were chosen. Differences are then noticeable according to the different qualitative parameters chosen in the study. Moreover, correlations, already observed in the literature for quantitative variables, are confirmed. On the other hand, differences appear which may suggest that the models used are inappropriate for certain materials. Epoxy ; Diffusion ; Materials science ; Statistical analysis ; Ageing ; Statistics ; Thermodynamics ; Composite material ; Mathematics ; Medicine ; Physics Natural Fiber Reinforced Composites ; Epoxy Resin Curing Processes ; Mechanical Behavior of Composites
Authors: Szende Tonk | Eszter Rápó
Source: International Journal of Molecular Sciences (article, 2022-10-05)
Field: Chemistry — Analytical Chemistry

Linear and Nonlinear Regression Analysis for the Adsorption of Remazol Dye by Romanian Brewery Waste By-Product, Saccharomyces cerevisiae Earth's water balance and economy are becoming increasingly fragile due to overpopulation, global warming, severe environmental pollution and both surface and groundwater pollution. Therefore, it is essential to find solutions to the problems of water scarcity and water pollution. In this research, an experiment was designed to optimize the technique for the adsorption of Remazol Red F3B (RR) dye by lyophilized brewery yeast waste from the fermentation process. Moreover, we proved that brewery yeast is a great adsorbent. Batch adsorption experiments were carried out for optimization of different initial parameters, such as initial dye concentration (5-1000 mg/L), amount of yeast (0.5-2.5 g), pH (3-11) and temperature (20 to 40 °C). Furthermore, the structure and elemental composition of the adsorbent were analyzed with SEM, EDS and FTIR before and after biosorption. The best fits for the mathematical isotherm models in the case of the linear form were the Langmuir I and Freundlich models (R<sup>2</sup> = 0.923 and R<sup>2</sup> = 0.921) and, for the nonlinear form, the Khan model (R<sup>2</sup> = 0.9996) was the best fit. The pseudo-second-order kinetic model showed the best fit for both linear (plotting t/q<sub>t</sub> vs. t) and nonlinear forms, are the calculated q<sub>e</sub> values were similar to the experimental data. Adsorption ; Biosorption ; Freundlich equation ; Langmuir ; Chemistry ; Yeast ; Pollution ; Environmental pollution ; Fermentation ; Wastewater ; Langmuir adsorption model ; Pulp and paper industry ; Mathematics ; Environmental science ; Nuclear chemistry ; Environmental engineering ; Environmental chemistry ; Food science ; Organic chemistry ; Biochemistry ; Engineering ; Biology ; Ecology Dye analysis and toxicity ; Adsorption and biosorption for pollutant removal ; Water Quality Monitoring and Analysis