jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiaoqing Pan | Chaitanya Gadre | Xingxu Yan | Qichen Song | Jie Li | Lei Gu | Toshihiro Aoki | Sheng‐Wei Lee | Gang Chen | Ruqian Wu
Source: Research Square (preprint, 2021-05-25)
Field: Materials Science — Materials Chemistry

Nanoscale Imaging of Phonon Dynamics by Electron Microscopy Abstract Spatially resolved vibrational mapping of nanostructures is indispensable to the development and understanding of thermal nanodevices1, modulation of thermal transport2, and novel nanostructured thermoelectric materials3–5. Through the engineering of complex structures such as alloys, nanostructures, and superlattice interfaces, one can significantly alter the propagation of phonons and suppress material thermal conductivity while maintaining electrical conductivity2. Probing local vibrations and phonon dispersions in nanostructured semiconductors informs structure-property correlations and offers insights into the design and optimization of novel thermoelectric materials. There have been no correlative experiments that spatially track the modulation of phonon properties in and around nanostructures due to spatial resolution limitations of conventional optical phonon detection techniques. Here we demonstrate two-dimensional spatial mapping of phonons in a single silicon-germanium (SiGe) quantum dot (QD) using monochromated electron energy loss spectroscopy (EELS) in the transmission electron microscope (TEM). Tracking the variation of the Si optical mode in and around the QD, we observe the nanoscale modification of the composition induced redshift. We observe nonequilibrium phonons that only exist near the interface and furthermore, develop a novel technique to differentially map phonon momenta providing direct evidence that the interplay between diffusive and specular reflection largely depends on the detailed atomistic structure --a major advancement in the field. Our work unveils the nonequilibrium phonon dynamics at nanoscale interfaces and can be used to study actual nanodevices and aid in the understanding of heat dissipation near nanoscale hotspots, which is crucial for future high-performance nanoelectronics. Our work demonstrates high spatial resolution vibrational characterization of nanostructures and interfaces that can be extended to other nanostructures and superlattice systems, in terms of composition, composition gradient, and structure driven phonon dynamics. Nanoscopic scale ; Phonon ; Dynamics (music) ; Microscopy ; Materials science ; Electron microscope ; Nanotechnology ; Condensed matter physics ; Chemical physics ; Physics ; Optics Thermal properties of materials ; Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies
Authors: Mazin Nabih Ali
Source: Al-Nahrain Journal for Engineering Sciences (article, 2021-06-27)
Field: Materials Science — Biomaterials

Study the Effect of Corrosion and Scale Inhibitors on Corrosion Rate of Carbon Steel in Cooling Towers Unit in Oil Refineries In the present work the effect of Corrosion &amp; Scale Inhibitor was evaluated by using of the commercial product (Kurita S2050) that mainly containing of (Na2HPO4) sodium phosphate as corrosion inhibitor and (C6H11NaO7) sodium glocunate as scale inhibitor &amp; dispersant. The dosing rate of this chemical was controlled according to the treatment system depend mainly on the monitoring of LI &amp; RI indexes for (30) days treatment in the cooling tower unit of Al-Dora Oil refinery-Baghdad. The corrosion rate and the corrosion inhibitors efficiency were calculated by measurement of weight loss in standard test coupon (AISI 1010). After 30 day of the Field Test, the result show that the treatment program performance was effective in the corrosion &amp; scale inhibition through an acceptable corrosion rate less than 0.018 in gmd. Also the result of corrosion rate was analyzed statistically by using of (ANN) to formulate a prediction equation to corrosion rate identification. Corrosion ; Materials science ; Metallurgy ; Dispersant ; Cooling tower ; Oil refinery ; Corrosion inhibitor ; Carbon steel ; Sodium bicarbonate ; Water cooling ; Refinery ; Sodium ; Dispersion (optics) ; Chemistry ; Organic chemistry Calcium Carbonate Crystallization and Inhibition
Authors: Shantanu Shahane | Yuchen Shen | Sophie Wang
Source: arXiv (Cornell University) (preprint, 2021-03-03)
Field: Materials Science — Surfaces, Coatings and Films

Numerical Simulations of Frost Growth Using Mixture Model on Surfaces with Different Wettability Frost growth on cold surfaces is a transient process with coupled heat and mass transfer. Due to multiple factors such as humidity, temperature, flow velocity and constantly changing thermal properties as frost grows, precise prediction can be challenging. Especially when the geometry of the frosting surfaces gets complicated, it requires a balance of computing accuracy and efficiency. In this work, a numerical model is developed to predict frost growth considering the effect of the above parameters. Mixture model is adapted to improve the computational efficiency and the unstructured grids add the flexibility to extend the model to complex geometries. The predicted frost growth rate matches well with the experimental data reported in the literature under similar conditions. The model predicts reasonable growth trend of frost as the surface temperature, air temperature, humidity and flow velocity vary. The surface wettability effect is well captured at the early stage of frosting and it shows a higher frost growth rate on surfaces with a higher wettability. Frost (temperature) ; Wetting ; Humidity ; Relative humidity ; Materials science ; Mechanics ; Flexibility (engineering) ; Work (physics) ; Airflow ; Thermal ; Heat transfer ; Flow (mathematics) ; Mass transfer ; Environmental science ; Meteorology ; Thermodynamics ; Composite material ; Mathematics ; Physics Surface Modification and Superhydrophobicity ; Icing and De-icing Technologies ; Fluid Dynamics and Thin Films
Authors: Kritika Mishra Prakanshu Srivastava | Vivek Kumar Sahu and Pawan Kumar Pal
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2021-01-13)
Field: Chemistry — Analytical Chemistry

PLANT DISEASE DETECTION USING CONVOLUTIONAL NEURAL NETWORK When plants and crops are suffering from pests it affects the agricultural production of the country. Usually, farmers or experts observe the plants with eye for detection and identification of disease. But this method is often time processing, expensive and inaccurate. Automatic detection using image processing techniques provide fast and accurate results. This paper cares with a replacement approach to the development of disease recognition model, supported leaf image classification, by the utilization of deep convolutional networks. Advances in computer vision present a chance to expand and enhance the practice of precise plant protection and extend the market of computer vision applications within the field of precision agriculture. a completely unique way of training and therefore the methodology used facilitate a fast and straightforward system implementation in practice. All essential steps required for implementing this disease recognition model are fully described throughout the paper, starting from gathering images to make a database, assessed by agricultural experts, a deep learning framework to perform the deep CNN training. This method paper may be a new approach in detecting plant diseases using the deep convolutional neural network trained and finetuned to suit accurately to the database of a plants leaves that was gathered independently for diverse plant diseases. The advance and novelty of the developed model dwell its simplicity healthy leaves and background images are in line with other classes, enabling the model to distinguish between diseased leaves and healthy ones or from the environment by using CNN. Plants are the source of food on earth. Infections and diseases in plants are therefore a big threat, while the foremost common diagnosis is primarily performed by examining the plant body for the presence of visual symptoms [1]. As an alternative to the traditionally time-consuming process, different research works plan to find feasible approaches towards protecting plants. In recent years, growth in technology has engendered several alternatives to traditional arduous methods [2]. Deep learning techniques are very successful in image classification problems.\n\n Convolutional neural network ; Computer science ; Artificial intelligence ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Phan Xuan Le | Le Nguyen Hoa Binh
Source: Bulletin of Electrical Engineering and Informatics (article, 2021-07-07)
Field: Materials Science — Materials Chemistry

Effects of NaB&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;4&lt;/sub&gt;:Mn&lt;sup&gt;2+&lt;/sup&gt; and Ba&lt;sub&gt;2&lt;/sub&gt;Li&lt;sub&gt;2&lt;/sub&gt;Si&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;7&lt;/sub&gt;:Sn&lt;sup&gt;3+&lt;/sup&gt;,Mn&lt;sup&gt;2+&lt;/sup&gt; phosphors and remote structure organizations on the white light-emitting diodes with quantum dots and phosphors In order to increase the optical features of white light-emitting diodes (WLEDs), quantum dots (QDs) and phosphor materials have been proposed because of outstanding performance. The configuration of WLEDs with QDs layer and phosphor-silicone layer suggested placing these components separately to limit light loss, and enhance consistency at contact surface of QDs. In this research, the effects of QDs and phosphor on the performance of WLEDs are concluded through experiments. The emitted light and PL spectra were examined thoroughly, and infrared thermal imagers were applied to simulate the heat generation of an actual WLED device. The results show that with the configuration of 60 mA energy source, WLEDs which has the QDs-on-phosphor form attained luminous efficiency (LE) of 110 lm/W, with color rendering index (CRI) of Ra=92 and R9=80, whereas the WLEDs which has the phosphor-on-QDs form only has 68 lm/W in LE, Ra=57 and R9=24. Furthermore, WLEDs which has the QDs-on-phosphor form has less high temperature generated at the components’ conjunction in comparison to the counterpart, the peak generated heat in QDs-on-phosphor WLEDs is also lower and the heating capacity gap between 2 structures can go up to 12.3°C. Phosphor ; Luminous efficacy ; Materials science ; Diode ; Color rendering index ; Color temperature ; Optoelectronics ; Light-emitting diode ; Analytical Chemistry (journal) ; Optics ; Chemistry ; Layer (electronics) ; Nanotechnology ; Physics Luminescence Properties of Advanced Materials
Authors: Luis Rangel DaCosta | Mary Scott
Source: Microscopy and Microanalysis (article, 2021-07-30)
Field: Materials Science — Materials Chemistry

Construction Zone: a software package for building complex nanoscale atomic scenes for applications in machine learning data generation pipelines An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button. Pipeline transport ; Computer science ; Nanoscopic scale ; Software ; Materials science ; Engineering ; Nanotechnology ; Mechanical engineering ; Operating system Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Advanced Materials Characterization Techniques
Authors: Chathuri Chandani Silva
Source: IRL - University of Missouri, St. Louis (University of Missouri–St. Louis) (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Computational studies of carbon nanocluster solidification A subset of micron-size meteoritic carbon particles formed in red giant atmospheres show a core-rim structure, likely condensed from a vapor phase into super-cooled carbon droplets that nucleated graphene sheets (~40Å) on randomly oriented 5-atom loops during solidification, followed by coating with a graphite rim. Similar particles form during slow cooling of carbon vapor in the lab. Here we investigate the nucleation and growth of carbon rings and graphene sheets using density functional theory (DFT). Our objectives: (1). explore different computational techniques in DFT-VASP for various carbon structures and compare the results with literature, (2). investigate the nucleation and growth of carbon rings and graphene sheets at the experimental 1.8 g/cc density estimate, by supercell relaxation of randomized liquid-like carbon atom clusters, and (3). Compare carbon cluster energies for combinations of DFT-VASP and long-range carbon bond order potential (LCBOP) relaxations. Observations show: (a) that 29 atom diamond clusters relax into the C28 fullerene with a central carbon atom, (b) new evidence for the instability of an Fm3m carbon phase with the diamond unit cell, and (c) that pent-loop formation is energetically favored over hex-loop formation in a relaxed melt. Literature work on the effectiveness of pent-loops as nucleation seed for graphene structures, plus the fact that each pent-loop can give rise to 5 differently oriented sheets, helps explain electron-microscope data on graphene-sheet number densities and provides guidance for nucleation/growth models being developed. Carbon fibers ; Materials science ; Composite material Carbon Nanotubes in Composites ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry ; Fullerene Chemistry and Applications
Authors: Jun Lu | Chaofan Cui | Qihao Yu | Juanjuan Su | Jian Han
Source: Research Square (preprint, 2021-05-14)
Field: Materials Science — Surfaces, Coatings and Films

Robustly superhydrophobic polylactic acid nonwoven membranes for efficient oil/water separation Abstract Oily wastewater is an urgent issue threatening the ecosystem and human health. Superhydrophobic porous materials are widely concerned as promising candidates for effective oil/water separation and oil adsorption. However, superhydrophobic porous materials are still confronted with frustrations such as complex preparation processes and secondary pollution to the environment. Superhydrophobic porous materials with biodegradability and a relatively simple preparation process are more attractive to practical application and environmental protection. In this work, biodegradable and industrially applied polylactic acid (PLA)nonwoven materials were used as porous membranes, then PLA nanoparticles were loaded on the membrane surface to construct the hierarchical rough structure. The modified PLA nonwoven membrane (Nano-PLA) shows superhydrophobicity and efficient oil/water separation performance. Moreover, strong mechanical strength and acceptable toughness are obtained. This work offers an easily controlled and industrially used pathway for the design of robust, highly selective, and biodegradable oil/water separation materials. Polylactic acid ; Materials science ; Membrane ; Porosity ; Biodegradation ; Chemical engineering ; Adsorption ; Environmental pollution ; Nanotechnology ; Composite material ; Polymer ; Organic chemistry ; Chemistry ; Environmental science ; Engineering Surface Modification and Superhydrophobicity ; Advanced Sensor and Energy Harvesting Materials ; Electrospun Nanofibers in Biomedical Applications
Authors: C Lai | L Yu | J Leburton | K Lei | D Leipold | R See Nikandish | G Li | P Li | Z Wang | H Yu | F Wang | L Liu | Jung Li | W | Y Li | A Liu | C Lin | J Lin | N Blum | F Liou | Y Liou | Y See Wan | K Singh | Y Huang | T Ahmed | C Ting | S Samukawa | H Kuo | S Liu | E Lopez-Naranjo | A See Alvarado-Aramburo | D Mencarelli | L Pierantoni | M Modreanu | M See Dragoman | C Moore | M Xu | J Morris | R Nikandish | E Blokhina | R Staszewski | A Nisar | G Verma | N Bindal | J Norman | J Reithmaier | S Bauer | T Riley | D Beahm | R Sarpeshkar | T Septon | B Sheu | X Jiang | S Kao | V Sichkovskyi
Source: IEEE Nanotechnology Magazine (article, 2021-12-01)
Field: Materials Science — Materials Chemistry

2021 Index IEEE Nanotechnology Magazine Vol. 15 This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index. Index (typography) ; Nanotechnology ; Materials science ; Computer science ; World Wide Web Advanced Nanomaterials in Catalysis ; Graphene and Nanomaterials Applications
Authors: Zhi Shen | Jianwu Yan | Kang Jin | Kai Fu | Yingli Zhou
Source: Journal of Sensors (article, 2021-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Composition Regulation and Microstructure Characterization of Fe<sub>100-x</sub>Ga<sub>x</sub> Films in the Manufacturing Industry Fe 100-x Ga x giant magnetostrictive films (GMF) are attracting ever increasing attention for their potential application to manufacturing integrated magnetostrictive displacement sensors. However, it is difficult to fabricate Fe 100-x Ga x thin films with different compositions at will. The influence of compositions on alloy phases, grain sizes, film surface roughness, and magnetic domains of the films and magnetization of magnetron sputtered Fe 100-x Ga x films was investigated. Changing the ratio of the pure iron slice areas to alloy target areas, the desired film composition was achieved by the improved Mosaic method. The morphologies, magnetic domain structure, microstructure, and compositions of Fe 100-x Ga x films revealed by SEM, EDS, XRD, MFM, VSM, and TEM. The results show that there are &lt;1 1 0 &gt; texture in magnetron sputtered Fe 100-x Ga x films. The sharp peak attributed to the A 2 microstructure suggests that the film is crystalline. The magnetic domain structure of Fe 100-x Ga x films presents a network form, and the domain width decreases with the decrease of gallium content. It is also found that the magnetic domains of the films are not uniform. The TEM result shows that there are some strip patterns in the films, and the diffraction ring is discontinuous because of the structure extinction. For a suitable candidate of microdevice applications in MEMS, the optimum composition film should be Fe 83.25 Ga 16.75 film. Characterization (materials science) ; Microstructure ; Materials science ; Metallurgy ; Composition (language) ; Manufacturing engineering ; Crystallography ; Nanotechnology ; Engineering ; Chemistry ; Art Magnetic Properties and Applications ; Non-Destructive Testing Techniques ; Microstructure and Mechanical Properties of Steels
Authors: Yahjeb Bouha Khatraty | Nédra Mellouli Nauwynck | Mamadou Diallo
Source:  (article, 2021-07-20)
Field: Chemistry — Analytical Chemistry

REPORT ON ESTIMATING RICE FIELD QUALITY USING ARTIFICIAL INTELLIGENCE The use of artificial intelligence has made life easier for farmers, as analysis of agricultural data allows farmers to makeinformed decisions, supported by large data sets and processed by machine learning algorithms. In this paper, we presentthe Computer science ; Field (mathematics) ; Artificial intelligence ; Machine learning ; Quality (philosophy) ; Agriculture ; Artificial neural network ; Artificial Intelligence System ; Mathematics Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Smart Agriculture and AI
Authors: Wan Sieng Yeo
Source: Research Square (preprint, 2021-07-06)
Field: Materials Science — Polymers and Plastics

Least Square Support Vector Regression-Based Model for Whiteness Index of Cotton Fabric Prediction Abstract The textile bleaching process uses a hydrogen peroxide (H 2 O 2 ) solution in alkali pH associated with high temperature is the commonly used bleaching procedure in cotton fabric manufacture. The purpose of the bleaching process is to remove the natural colour from cotton to obtain a permanent white colour before dyeing or shape matching. Normally, the visual ratings of whiteness on the cotton are measured by the whiteness index (WI). Notice that lesser research study is focusing on chemical predictive modelling of the WI of cotton fabric than its experimental study. Predictive analytics using predictive modelling can forecast the outcomes that can lead to better-informed cotton quality assurance and control decisions. Up to date, limited study applying least square support vector regression (LSSVR) based model in the textile domain. Hence, the present study was aimed to develop the LSSVR-based model, namely multi-output LSSVR (MLSSVR) using bleaching process variables to predict the WI of cotton. The predictive accuracy of the MLSSVR model is measured by root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R 2 ), and its results are compared with other regression models including partial least square regression, predictive fuzzy model, locally weighted partial least square regression and locally weighted kernel partial least square regression. The results indicate that the MLSSVR model performed better than other models in predicting the WI as it has 60–1209% lower values of RMSE and MAE as well as it provided the highest R 2 values which are up to 0.9985. Index (typography) ; Square (algebra) ; Regression analysis ; Mathematics ; Regression ; Support vector machine ; Statistics ; Computer science ; Artificial intelligence ; Geometry Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Dyeing and Modifying Textile Fibers
Authors: Maria Frizzarin | Antonio Bevilacqua | Bhaskar Dhariyal | Katarina Domijan | Federico Ferraccioli | Elena Hayes | Georgiana Ifrim | Agnieszka Konkolewska | Thach Le Nguyen | Uche Mbaka | Giovanna Ranzato | Ashish Singh | Marco Stefanucci | Alessandro Casa
Source: Chemometrics and Intelligent Laboratory Systems (preprint, 2021-10-25)
Field: Chemistry — Analytical Chemistry

Mid infrared spectroscopy and milk quality traits: A data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2021” A chemometric data analysis challenge has been arranged during the first edition of the “International Workshop on Spectroscopy and Chemometrics”, organized by the Vistamilk SFI Research Centre and held online in April 2021. The aim of the competition was to build a calibration model in order to predict milk quality traits exploiting the information contained in mid-infrared spectra only. Three different traits have been provided, presenting heterogeneous degrees of prediction complexity thus possibly requiring trait-specific modelling choices. In this paper the different approaches adopted by the participants are outlined and the insights obtained from the analyses are critically discussed. Chemometrics ; Competition (biology) ; Quality (philosophy) ; Trait ; Calibration ; Spectroscopy ; Infrared spectroscopy ; Computer science ; Mathematics ; Chemistry ; Statistics ; Biology ; Ecology ; Machine learning ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Meat and Animal Product Quality