jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qing He | Dongdong Zhu | Xiaocheng Wu | Duo Dong | Xiaoying Jiang | Meng Xu
Source: Preprints.org (preprint, 2019-04-15)
Field: Materials Science — Materials Chemistry

The Dehydrogenation Mechanism and Reversibility of LiBH&lt;sub&gt;4&lt;/sub&gt; Doped by Active Al* Derived from AlH&lt;sub&gt;3&lt;/sub&gt; A detailed analysis of the dehydrogenation mechanism and reversibility of LiBH4 doped by active Al* derived from AlH3 was performed by thermogravimetry (TG), differential scanning calorimetry (DSC), mass spectral analysis (MS), powder X-ray diffraction (XRD), scanning electronic microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The results show that the dehydrogenation of LiBH4/Al* is a five-step reaction: (1) LiBH4 + Al &amp;rarr; LiH + AlB2 + &amp;ldquo;Li-Al-B-H&amp;rdquo; + B2H6 + H2; (2) the decomposition of "Li-Al-B-H" compounds liberating H2; (3) 2LiBH4 + Al &amp;rarr; 2LiH + AlB2 + 3H2; (4) LiBH4 &amp;rarr; LiH + B + 3/2H2; (5) LiH + Al &amp;rarr; LiAl + 1/2H2. And the reversibility of LiBH4/Al* composite is based on equation as follows: LiH + LiAl + AlB2 + 7/2H2 &amp;harr; 2LiBH4 + 2Al. The extent of dehydrogenation reaction between LiBH4 and Al* greatly depends on the precipitation and growth of reaction products (LiH, AlB2 and LiAl, etc.) on the surface of Al*. A passivation shell of Al* formed by these products is the kinetic barrier to the dehydrogenation of LiBH4/Al* composite. Dehydrogenation ; Differential scanning calorimetry ; Thermogravimetry ; Decomposition ; Fourier transform infrared spectroscopy ; Materials science ; Hydrogen ; Chemistry ; Analytical Chemistry (journal) ; Nuclear chemistry ; Physical chemistry ; Crystallography ; Chemical engineering ; Inorganic chemistry ; Catalysis ; Organic chemistry ; Thermodynamics ; Physics Hydrogen Storage and Materials ; Superconductivity in MgB2 and Alloys ; Superconducting Materials and Applications
Authors: Adriana Samide | Claudia Merişanu | Bogdan Tutunaru | Gabriela Eugenia Iacobescu
Source: Preprints.org (preprint, 2019-12-20)
Field: Materials Science — Materials Chemistry

Poly(Vinyl Butyral-co-Vinyl Alcohol-co-Vinyl Acetate) Coating Performance on Copper Corrosion in Saline Environment Poly(vinyl butyral-co-vinyl alcohol-co-vinyl acetate) named further PVBA was investigated as protective coating for copper corrosion in 0.9 % NaCl solution using electrochemical measurements such as, electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization associated with Atomic Force Microscopy (AFM). The PVBA coating on the copper surface (Cu-PVBA) was modeled in methanol containing PVBA. Its inhibitory properties against corrosion was comparatively discussed with those of the copper sample treated in methanol without polymer (Cu-Me) and of untreated sample (standard copper). A protective performance of PVBA coating of 80 % was computed from electrochemical measurements, for copper corrosion in NaCl solution. Also, AFM images designed a specific surface morphology of coated surface with PVBA, clearly highlighting a polymer film adsorbed on the copper surface, which presents certain deterioration after corrosion, but metal surface was not significantly affected compared to those of untreated samples or treated in methanol, in the absence of PVBA. Vinyl alcohol ; Copper ; Dielectric spectroscopy ; Corrosion ; Vinyl acetate ; Materials science ; Coating ; Electrochemistry ; Methanol ; Polymer ; Polarization (electrochemistry) ; Adsorption ; Chemical engineering ; Inorganic chemistry ; Metallurgy ; Composite material ; Chemistry ; Electrode ; Organic chemistry Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Asphalt Pavement Performance Evaluation
Authors: Jessica C. Ortiz-Rodríguez | Juan A. Santana | Dalvin D. Méndez‐Hernández
Source: ChemRxiv (preprint, 2019-10-21)
Field: Chemistry — Organic Chemistry

Linear Correlation Models for the Redox Potential of Organic Molecules in Aqueous Solutions &lt;p&gt;In this study we use the molecular orbital energy approximation (MOEA) and the energy difference approximation (EDA) to build linear correlation models for the redox potentials of 53 organic compounds in aqueous solutions. The molecules evaluated include nitroxides, phenols and amines. Both the MOEA and EDA methods yield similar correlation models, however the MOEA method is less computationally expensive. Correlation coefficients (R2) below 0.3 and mean absolute errors above 0.25 V were found for correlation models built without solvent effects. When explicit water molecules and a continuum solvent model are added to the calculations, correlation coefficients close to 0.8 are reached and mean absolute errors below 0.18 V are obtained. The incorporation of solvent effects is necessary for good correlation models, particularly for redox processes of charged molecules in aqueous solutions. A comparison of the correlation models from different methodologies is provided.&lt;br&gt;&lt;/p&gt; Aqueous solution ; Molecule ; Redox ; Solvent ; Chemistry ; Linear correlation ; Correlation ; Solvent effects ; Correlation coefficient ; Computational chemistry ; Yield (engineering) ; Organic molecules ; Thermodynamics ; Physical chemistry ; Mathematics ; Physics ; Organic chemistry ; Statistics Free Radicals and Antioxidants ; Thermal and Kinetic Analysis ; Inorganic and Organometallic Chemistry
Authors: Chun Soo Park
Source: eScholarship (California Digital Library) (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Prediction of High-Performance Thermoelectric Materials and Optimal Electronic Structures for Thermoelectricity The thermoelectric figures of merit of bulk materials up to date have not overcome zT = 3, and only in rare occasions have they surpassed zT = 2. Bulk thermoelectrics with zT &amp;gt; 3 have been desired but have not yet been theoretically predicted let alone experimentally realized. In this doctoral work, high-performance thermoelectric materials theoretically capable of zT &amp;gt; 4 are identified and characterized using state-of-the-art first-principles com- putational methods based on density-functional theory. Ba2BiAu and Sr2BiAu full-Heusler compounds in particular are predicted to deliver ultrahigh thermoelectric performances – the latter across all temperature domain from cryogenic to high: 0.3 ≤ zT ≤ 5 at 100 K ≤ T ≤ 800 K. While unfortunately the compounds look not n-dopable and their predicted zT values inaccessible, they constitute a theoretical proof of concept that zT &amp;gt; 4 is within reach for bulk compounds. With the lessons learned from these compounds and others, the optimal electronic structures for intrinsic thermoelectric performance are generally determined for both semiconductors and metals. Highly dispersive bands at off-symmetry points that min- imize electron-phonon scattering is optimal for semiconductors, while a flat-and-linear band crossing that leads to electron filtering and high Seebeck coefficients is optimal for metals. May these generalizations help propel discoveries of more high-performance thermoelectrics. Thermoelectric effect ; Thermoelectric materials ; Condensed matter physics ; Figure of merit ; Seebeck coefficient ; Semiconductor ; Materials science ; Engineering physics ; Work (physics) ; Density functional theory ; Optoelectronics ; Physics ; Thermodynamics ; Quantum mechanics Advanced Thermoelectric Materials and Devices ; Heusler alloys: electronic and magnetic properties ; Topological Materials and Phenomena
Authors: Ziqing Du | Abhishek Gupta | Christian Clarke | Matt Cappadana | David Clases | Deming Liu | Zhuoqing Yang | Philip Doble | Bill Price | Xiaoxue Xu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-11-22)
Field: Materials Science — Materials Chemistry

Porous upconversion nanostructures as bimodal biomedical imaging contrast agents Abstract Lanthanide ions doped upconversion nanoparticles (UCNPs) hold great promise as the imaging contrast agent for multimodal medical imaging techniques for diagnosis, including fluorescent bioimaging, magnetic resonance imaging, and computed tomography. However, the maximized signal values of fluorescence and MRI cannot be achieved simultaneously from the same upconversion nanoparticles structures because high specific surface areas can benefit the signal gaining of MRI while big size can induce brighter fluorescent imaging. In this work, we designed and fabricated novel core-porous shell structures for UCNPs with much-enhanced signal values for both fluorescent imaging and MRI. The core-porous shell UCNPs were synthesized via a post-treatment process after an inert shell was coated onto the core UCNPs. The formation mechanism was carefully investigated. The fluorescent and magnetic resonance properties have been detailed characterized and compared from core, core-shell and core-porous UCNPs. Large and bright UCNPs in fluorescence and MRI have been achieved and great potential as the dual-modal contrast agent. Materials science ; Fluorescence ; Magnetic resonance imaging ; Photon upconversion ; Nanoparticle ; Nanotechnology ; Fluorescence-lifetime imaging microscopy ; Core (optical fiber) ; SIGNAL (programming language) ; Porous medium ; Porosity ; Luminescence ; Optoelectronics ; Optics ; Computer science ; Radiology Luminescence Properties of Advanced Materials ; Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics
Authors: Line Pouchard | Kerstin Kleese van Dam | Stuart I. Campbell
Source: International Journal of Digital Curation (article, 2019-09-11)
Field: Materials Science — Materials Chemistry

Experimental Data Curation at Large Instrument Facilities with Open Source Software The National Synchrotron Light Source II operating at Brookhaven National Laboratory since 2014 for the US Department of Energy is one of the newest and brightest storage-ring synchrotron facility in the world. NSLS-II, like other facilities, provides pre-processing of the raw data and some analysis capabilities to its users. We describe the research collaborations and open source infrastructure developed at large instrument facilities such as NSLS-II for the purpose of curating high value scientific data along the early stages of the data lifecycle. Data acquisition and curation tasks include storing experiment configuration, detector metadata, raw data acquisition with infrastructure that converts proprietary instrument formats to industry standards. In addition, we describe a specific effort for discovering sample information at NSLS-II and tracing the provenance of analysis performed on acquired images. We show that curation tasks must be embedded into software along the data life cycle for effectiveness and ease of use, and that loosely defined collaborations evolve around shared open source tools. Finally we discuss best practices for experimental metadata capture in such facilities, data access and the new challenges of scale and complexity posed by AI-based discovery for the synthesis of new materials. Metadata ; Computer science ; Raw data ; Software ; National laboratory ; Data acquisition ; Tracing ; Data science ; World Wide Web ; Database ; Operating system ; Engineering Machine Learning in Materials Science ; Scientific Computing and Data Management ; Research Data Management Practices
Authors: Pavel N. Zolotarev | Nadezhda A. Nekrasova | Andrey A. Golov | Roman A. Eremin
Source: EPJ Web of Conferences (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

A combined DFT/topological analysis approach for modeling disordered solid electrolytes In the scope of this study, the Ag2S·CdS·3SnS2 solid electrolyte disordered in the Cd/Sn sublattice is explored by means of the approach involving configurational space (CS) setting and first-principles calculations. Within the density functional theory calculations on the CS, the absolute differences in Ag vacancy formation energies up to 2.6 eV/cell were obtained for possible Cd/Sn dispositions. Subsequently, silver ion migration was modeled using the nudged elastic band method. The migration energies in the range of 0.250 to 2.993 eV/cell were obtained. By application of topological descriptors, namely, the relative disposition of Cd atoms and the number of Cd atoms in the vicinity of Ag vacancy, the reliable correlations were obtained between the Cd/Sn relative disposition and the calculated energy characteristics. Vacancy defect ; Density functional theory ; Electrolyte ; Ion ; Chemistry ; Space (punctuation) ; Topology (electrical circuits) ; Fast ion conductor ; Range (aeronautics) ; Chemical physics ; Crystallography ; Materials science ; Computational chemistry ; Physical chemistry Solid-state spectroscopy and crystallography ; Machine Learning in Materials Science ; Chalcogenide Semiconductor Thin Films
Authors: Behnoosh Khataei
Source: Determinations in nanomedicine & nanotechnology. (article, 2019-10-15)
Field: Chemistry — Organic Chemistry

Optimizing the Annealing Effect of Zn/Ac Nanoparticle Synthesis on Dye Wastewater Treatment by Combination of Ultrasonic and Photocatalytic Methods Many different environmental researches were done on the treatment of water, wastewater and air pollutants by different biological, physical and chemical processes.Pollution of water sources by dye pollutants from various industries such as textile, paper, rubber and plastic industries is a major environmental problem.Organic dyes cause irreparable damage to the environment due to the avoiding the light entry to water, disruption of photosynthesis, reduction of oxygen transfer to water, occurrence of eutrophication, interference with the ecology of the receiving waters, toxic effects as well as unpleasant appearance [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18].Different methods are used for the treatment of dye wastewater [19][20][21][22][23][24][25]. Photocatalysis ; Wastewater ; Nanoparticle ; Materials science ; Ultrasonic sensor ; Annealing (glass) ; Sewage treatment ; Chemical engineering ; Nuclear chemistry ; Nanotechnology ; Chemistry ; Environmental science ; Metallurgy ; Environmental engineering ; Catalysis ; Organic chemistry ; Acoustics ; Engineering ; Physics Nanomaterials for catalytic reactions
Authors: Hao He | Can Liu | Haiguang Liu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-07-03)
Field: Materials Science — Materials Chemistry

Model reconstruction from Small angle X-ray Scattering data using deep learning methods Abstract We present an algorithm based on a deep learning method for model reconstruction from small angle X-ray scattering (SAXS) data. An auto-encoder for protein 3D models was trained to compress 3D shape information into vectors of a 200-dimensional latent space, and the vectors are optimized using genetic algorithms to build 3D models that are consistent with the scattering data. The algorithm was implemented using Python with the TensorFlow framework and tested with experimental data, demonstrating capacity and robustness of accurate model reconstruction even without using prior model size information. Synopsis A deep learning method based on the auto-encoder framework for model reconstruction from small angle scattering data Python (programming language) ; Robustness (evolution) ; Small-angle X-ray scattering ; Scattering ; Encoder ; Computer science ; Artificial intelligence ; Deep learning ; Algorithm ; 3d model ; Autoencoder ; Small-angle scattering ; Computer vision ; Pattern recognition (psychology) ; Machine learning ; Optics ; Physics Enzyme Structure and Function ; Protein Structure and Dynamics ; Protein purification and stability
Authors: Mahasweta Mandal | Swati Bandyopadhyay
Source: International Journal of Computer Applications (article, 2019-07-18)
Field: Materials Science — Polymers and Plastics

To Predict the Waterfastness Rate of Foil Print Applying Artificial Neural Network The aim of this present study to evaluate the print quality by the waterfastness properties of foil prints which are exposed to water or rain. Waterfastness is an important property for any kind of packaging products, specially for food and medicine packages for assessing their print stability. The fastness properties of prints can be described in terms of print durability and image stability. Moreover, the poor fastness properties of prints will affect the product sale adversely. Little work has been done to study the fastness properties of printed films and foils. This study has preferred to take the blister foils as samples which are printed by gravure process as the blister foil has extensive usage in food and medicine packaging. Water immersion method and water spray methods both are used to study the water fastness of magenta ink on foil and the results were found to be similar. The evaluation is carried out by the measured spectral curves and colorimetric values before and after exposure using the oceanographic spectroradiometer (DH2000BAL) device. A significant change in reflectance in the blue and red regions with time indicates the fading of magenta print with time. This article has proposed a newly approach based on artificial neural network (ANN) model to determine the waterfastness rate of foil prints with variation of time. A comparative analysis is also made between the ANN model and regression model. However, the artificial neural network (ANN) has given a bit more excellent prediction than regression. In the context of prediction of waterfastness, the artificial neural network (ANN) model has given optimal results with the MSE -1.2409and a correlation coefficient of 0.9990.. Computer science ; Artificial neural network ; Artificial intelligence ; FOIL method ; Materials science Textile materials and evaluations ; Material Properties and Processing
Authors: Rencheeraj Mohan | K. Sreekumar
Source: International Journal of Computer Applications (review, 2019-04-11)
Field: Chemistry — Analytical Chemistry

A Literature Review on Machine Vision based Approaches for Ripeness Detection of Fruits Plump fruits are a vital part of the human diet giving mandatory vitamins, minerals and other health encouraging compounds. Quality assessment and finding of fruit ripeness is a major concern in agriculture business and becomes a growing research concern in computer vision. Image processing is an advanced field which led to a higher demand to reduce the high rate of errors and given more possible results. Therefore, the objective of many types of research is to standardize and reduce manual work in the classification of tomatoes ripeness. One of the most important feature of an image is color. Estimating the ripeness of fruits via color can be performed as it is the dominant feature in describing the information of the image. However, each color models have been given a different performance when used in the experiment. This paper is a survey of different techniques that are deployed over different varieties of fruit images in order to detect maturity stages for ripening, fruit region estimation and also, the effect of different color models and other features on detecting ripeness was studied in this literature survey. Ripeness ; Computer science ; Artificial intelligence ; Food science ; Chemistry Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Industrial Vision Systems and Defect Detection
Authors: Micaela Vannini | Paola Marchese | Laura Sisti | Annamaria Celli | Maura Ferri | Stefania Monari | Annalisa Tassoni | Maria Ehrnell | Lovisa Eliasson | Epameinondas Xanthakis | Taihua Mu | Hongnan Sun
Source: Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (article, 2019-01-01)
Field: Materials Science — Biomaterials

From wine pomace and potato wastes to novel PHA-based bio-composites: examples of sustainable routes for full valorisation of the agro-wastes Valorisation ; Pomace ; Wine ; Waste management ; Wine grape ; Pulp and paper industry ; Environmental science ; Biotechnology ; Food science ; Engineering ; Chemistry ; Biology biodegradable polymer synthesis and properties
Authors: R Velvizhi | R. Kavitha | C Geetha | S Sri | A Kumarave | Rangarajank | P Kavitha | S Prabakaran | A Kumaravel | Meeteio | P Dutta | Duttap | Kumaravela | J Tariq | M Sudha | G Ayyappan | C Nalini | K Kaliyamurthie | K Sivaraman | S Ramesh | P Balasubramanian | A Sangeetha | S Gayathiridevi | N Kumar | Shwtambarikharabe | M Vivekanandan | Dr Rajabhushanam | Dr | V Rajabhushanam | G Karthik | Vivek | K Rangaswamy | Dr Rajabhushanamc | R Kavitha | R Nedunchelian | G Kavitha | G Michael | A Chandrasekar | S Pothumani | M Sriram | J Sridhar | G Arul Selvan | Sridhar | N Priya | Anuradha | Khanna | B Sundarraj | M Senthil | V Khanna
Source: International Journal of Innovative Technology and Exploring Engineering (article, 2019-08-23)
Field: Materials Science — Materials Chemistry

Graphene a Fundamental of Interaction Globe Communication became certainly one of the integral parts into the social and development that is technical of beings. B ut, the downside that is biggest within the contemporary realm of interaction is that the quantity of people utilizing mobile, internet as well as other such interaction surroundings are increasing at a significant price. This contributes to greater bandwidth requirement and much more than that, greater rate of information transfer. Because, as the amount of users enhance, greater would be the strain o letter various products which form the infrastructure that is fundamental of interaction globe.Graphene, a product found by Nobel Prize champions Andre Geim and Konstantin Novoselov is a product which assists in working with these specific things. It's a two type that is dimensional of which includes unique properties which will help in increasing the d ata prices tremendously. The most crucial home of Graphene is the fact that sign moving through the products c an flow with speeds reater that is g the rate of light. One other properties[1] are its interestingly great energy and freedom that is superb. The products such as for example a ntennas, transistors, etc. developed by utilizing Graphene as the fundamental product g ive better and gratification that is efficient. A great many other products like batteries and touch screens are more versatile and efficient whenever developed by utilizing Graphene Globe ; Graphene ; Product (mathematics) ; Realm ; Computer science ; Telecommunications ; Bandwidth (computing) ; Nanotechnology ; Materials science ; Mathematics ; Political science ; Law ; Biology Material Selection and Properties ; Graphene research and applications ; Advanced Physical and Chemical Molecular Interactions
Authors: Silpa Susan Alex
Source: International Journal of Engineering Applied Sciences and Technology (article, 2019-10-01)
Field: Chemistry — Analytical Chemistry

PLANT SPECIES CLASSIFCATION USING BOF Automated plant species identification system could help botanists and layman for identifying plant species expeditiously. In this research, a BoF(Bag of Features) approach similar to that of deep learning is used to extract the features of the leaves and classify them hastily. 16 species are there in the dataset and in each species there are 30 images, so a total of 16 X 30, 480 images are in total. The leaf images are given as input and they undergoes different filtering techniques and segmentation, after that the image is fed into Bag of Features for feature extraction and classification. In olden days the shape, colour and the leaf vein morphometrics are used for feature extraction. Here the texture features of the leaves are used for extraction and classification. In addition to this, in this research the GLCM feature extraction method and Naive Bayes classification method is also used for comparing the result of Bag of Features approach. Using GLCM and Nave Bayes, get an accuracy of 89% in which in BoF 96% accuracy is obtained. From the research, we can conclude that the BoF can be an effective automated system for plant species identification. Environmental science Spectroscopy and Chemometric Analyses ; Face and Expression Recognition ; Smart Agriculture and AI