jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Bobby Umroh
Source: JOURNAL OF MECHANICAL ENGINEERING MANUFACTURES MATERIALS AND ENERGY (article, 2018-06-29)
Field: Materials Science — Materials Chemistry

Karakteristik permukaan dan struktur mikro Pada bahan aluiminium 6061menggunakan Pahat Karbida dengan metode pemesinan laju tinggi dan pemesinan kering Penelitian pemesinan laju tinggi dan kering dengan tujuan untuk kemasan permukaan yang meliputi corak permukaan cacat (defect) yang diakibatkan oleh kondisi pemesinan pada bahan aluminium 6061 menggunakan pahat karbida. Pengumpulan data pengujian pemesinan ini dilakukan menggunakan metode faktorial data sebanyak 8 kali percobaan dengan 3 variabel utama yaitu laju pemotongan(V), laju pemakanan (f) dan kedalaman potong (a) pada tiga tiga tingkat besaran. Dari percobaan yang telah direkomendasikan dengan kondisi pemesinan terbaik maka didapati beberapa Nilai kekasaran permukaan sangat ditentukan oleh aus pahat yang tinggi. Aus pahat yang tinggi (0.129-0.247)sangat berpotensi terjadi cacat berupa koyak permukaan (tearing surface) permukaan benda kerja termesin, pada laju pemakanan yang tinggi terjadi feed mark goresan karena laju pemakanan yang tinggi .Lebar butiran pada mikrostruktur sangat ditentukan oleh kecepatan potong, dimana pada kecepatan potong V= 1000 m/min besarnya butiran terlihat lebih melebar sedangkan pada V=1250 m/min besar butiran terlihat lebih rapat Physics ; Humanities ; Art Material Selection and Properties ; Additive Manufacturing and 3D Printing Technologies ; Aluminum Alloys Composites Properties
Authors: Abhijith | Pai Srinivasa | Grynal D’Mello | Hebbar Gautama
Source: MATEC Web of Conferences (article, 2018-01-01)
Field: Materials Science — Biomaterials

Surface roughness optimization in machining of AZ31 magnesium alloy using ABC algorithm Magnesium alloys serve as excellent substitutes for materials traditionally used for engine block heads in automobiles and gear housings in aircraft industries. AZ31 is a magnesium alloy finds its applications in orthopedic implants and cardiovascular stents. Surface roughness is an important parameter in the present manufacturing sector. In this work optimization techniques namely firefly algorithm (FA), particle swarm optimization (PSO) and artificial bee colony algorithm (ABC) which are based on swarm intelligence techniques, have been implemented to optimize the machining parameters namely cutting speed, feed rate and depth of cut in order to achieve minimum surface roughness. The parameter Ra has been considered for evaluating the surface roughness. Comparing the performance of ABC algorithm with FA and PSO algorithm, which is a widely used optimization algorithm in machining studies, the results conclude that ABC produces better optimization when compared to FA and PSO for optimizing surface roughness of AZ 31. Magnesium alloy ; Surface roughness ; Machining ; Materials science ; Metallurgy ; Surface finish ; Magnesium ; Computer science ; Mechanical engineering ; Algorithm ; Engineering drawing ; Composite material ; Engineering Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; Aluminum Alloy Microstructure Properties
Authors: Jamin Lee | Tae‐Jong Kim
Source: Journal of the Korean Wood Science and Technology (article, 2018-07-01)
Field: Chemistry — Organic Chemistry

Method of DNA Extraction from Pinus rigida Wood Pretreated with Sandpaper Species identification of wood provides important information for archaeology, restoration of cultural assets, preventing illegal logging, and more. Wood species are usually identified based on their anatomical features with the use of a microscope. However, this method may not be able to distinguish between anatomically similar species or subspecies. To overcome this problem, wood species need to be identified at the molecular level using DNA sequencing. However, unlike living plant cells, wood is difficult to pulverize using a mortar, and DNA extraction from dried wood is challenging. To solve these problems, we propose a pretreatment method in which wood is pulverized using 60-grit sandpaper and hydrated with water for 2 days. Using this method, we were able to stably amplify the rpoB gene from the extracted DNA of Pinus rigida. In addition, sequence analysis of the rpoB gene revealed six single nucleotide polymorphisms (SNPs), which classified the rpoB sequences in the genus Pinus into five groups. Our data indicate that although these SNPs were not suitable for species identification, they can potentially be used to determine the origin of different wood subspecies or individual samples of wood. rpoB ; Subspecies ; DNA extraction ; Sandpaper ; Species identification ; Biology ; DNA barcoding ; Pinus <genus> ; DNA sequencing ; Botany ; DNA ; Gene ; Polymerase chain reaction ; Materials science ; Evolutionary biology ; Zoology ; Composite material ; Genetics Wood and Agarwood Research ; Plant Pathogens and Fungal Diseases ; Genomics and Phylogenetic Studies
Authors: Hardeep Singh | Sandeep Sharma
Source: Asian Journal of Computer Science and Technology (article, 2018-08-05)
Field: Chemistry — Analytical Chemistry

Optimization of Fruit Disease Detection Process: Using Gaussian Filtering Along With Enhanced SVM Fruit disease detection becomes critical since economic and related issues are influenced through the healthy and non-healthy fruits. Technology has advanced and is used to primarily detect and abnormality which is not visible through the naked eye. This paper proposes a new technique of fruit disease detection at early stage for which Gaussian smoothening is used at pre-processing stage along with weighted kernel function within SVM for achieving higher classification accuracy. Feature extraction and selection mechanism uses rank based mechanism that allocates ranks on the basis of predictive significance. The result is obtained in terms of prediction accuracy and mean or average error. Result is optimized by the factor of 10%. Support vector machine ; Pattern recognition (psychology) ; Artificial intelligence ; Gaussian function ; Kernel (algebra) ; Computer science ; Gaussian process ; Feature extraction ; Gaussian ; Feature selection ; Mathematics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Carlos Romero | Fei Yang | Stella Raynova | L. Bolzoni
Source: Key engineering materials (article, 2018-05-11)
Field: Materials Science — Materials Chemistry

The Effect of Heat Treatments on Microstructure and Mechanical Properties of As-Extruded Ti-6Al-4V Alloy Rod from Blended Elemental Powders In this study, Ti-6Al-4V bars were first prepared by extrusion of powder compacts from blended powder mixtures in the beta phase region, then the as-extruded bars were heat-treated following four different conditions: beta quenching and aging (βQA), broken up structure (BUS) treatment, solution treatment and aging (STA) and recrystallization annealing (RA). The effect of the heat treatments on microstructure and mechanical properties was studied using optical microscopy, scanning electron microscopy, and mechanical test to determine which heat-treatment condition has the greatest impact on the mechanical properties of the as-extruded Ti-6Al-4V alloy. The results show that the as-extruded condition has the best balance of strength (1120 MPa of UTS) and ductility (11% of elongation to failure). βQA and STA lead to a slight increase in strength but ductility decreases considerably. After BUS and RA treatments, both strength and ductility are reduced. The relationship between processing, microstructure and properties was studied, and their implications towards fatigue behaviour and fracture toughness were discussed. Materials science ; Microstructure ; Alloy ; Extrusion ; Ductility (Earth science) ; Annealing (glass) ; Optical microscope ; Composite material ; Scanning electron microscope ; Elongation ; Toughness ; Quenching (fluorescence) ; Metallurgy ; Recrystallization (geology) ; Ultimate tensile strength ; Creep Titanium Alloys Microstructure and Properties ; Additive Manufacturing Materials and Processes ; Powder Metallurgy Techniques and Materials
Authors: Ekaterina N. Vervald | Kirill Laptinskiy | И. И. Власов | Olga A. Shenderova | Tatiana A. Dolenko
Source: Nanosystems Physics Chemistry Mathematics (article, 2018-02-12)
Field: Materials Science — Materials Chemistry

DNA-nanodiamond interactions influence on fluorescence of nanodiamonds In this study, the interaction between DNA and the surface of detonation nanodiamonds and nanodiamonds with NV centers is investigated, and the quantitative parameters of this interaction are calculated. The influence of interaction of DNA with nanodiamonds on the fluorescent properties of nanodiamonds is established. A correlation was found between the efficiency of DNA interaction with the surface of the detonation nanodiamonds and the changes of their fluorescence: the more DNA bonds with the nanodiamond surface groups -the stronger the fluorescence of detonation nanodiamonds increases in water. Nanodiamond ; Fluorescence ; Nanotechnology ; Materials science ; Biophysics ; Diamond ; Biology ; Physics ; Optics Diamond and Carbon-based Materials Research ; Analytical chemistry methods development
Authors: Marcin Jewiarz | Krzysztof Mudryk | Marek Wróbel | Anna Pociask
Source: Engineering for Rural Development (article, 2018-05-23)
Field: Chemistry — Analytical Chemistry

Agglomeration of dried <i>Ilex paraguariensis</i> for consumption purposes Nowadays, many products need to be transported long distances. The amount of material is in many cases limited by volume, especially if we take into account transport by sea. This way ready products or byproducts for beverages industry are imported from Asia, Africa or Southern America. The main streams seem to be tea and coffee, but there are other herbs. Such material is dried Ilex paraguariensis, which is used for brewing a special type of tea called Yerba Mate. Main countries, responsible for production are located in Southern America (Paraguay, Argentina and Brazil). Different than for coffee, the whole processing must be made on the place of cultivation. For transportation for long distances, densification of material seems to be a reasonable way to lower the cost of this operation. This paper presents a possibility of pressure agglomeration of Ilex paraguariensis for consumption. The impact of the agglomeration process has been analysed on the qualities of the drought product. The physical characteristics of the raw material have been determined, such as the grain size distribution and moisture content. Agglomeration tests were performed using different pressures and the study was conducted about absolute and envelope density, porosity and the Brazilian test to check the compressive strength of the pellets. As research material 4 blends available in the marked were used. The results presented in the paper show that there is a possibility of production of high quality granulates made from Ilex paraguariensis. What should be expected, the highest envelope density was obtained for the highest formation pressure. What needs to be mentioned, the pressure needed to achieve a good quality granule was even two times higher than in the case of other herbal materials. This was mainly due to stiff and tough structure of the material. Nevertheless, the results show that agglomeration of dried Yerba Mate can be an interesting form for long distance transportation. Economies of agglomeration ; Food science ; Pulp and paper industry ; Environmental science ; Chemistry ; Engineering ; Chemical engineering Heavy Metals in Plants ; Agricultural and Food Sciences ; Heavy metals in environment
Authors: Shaobo Cheng | Dong Zhang | Shiqing Deng | Xing Li | Jun Li | Guotai Tan | Yimei Zhu | Jing Zhu
Source: Applied Physics Letters (article, 2018-04-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Domain configurations in dislocations embedded hexagonal manganite systems: From the view of graph theory Topological defects and their interactions often arouse multiple types of emerging phenomena from edge states in Skyrmions to disclination pairs in liquid crystals. In hexagonal manganites, partial edge dislocations, a prototype topological defect, are ubiquitous and they significantly alter the topologically protected domains and their behaviors. Herein, combining electron microscopy experiment and graph theory analysis, we report a systematic study of the connections and configurations of domains in this dislocation embedded system. Rules for domain arrangement are established. The dividing line between domains, which can be attributed by the strain field of dislocations, is accurately described by a genus model from a higher dimension in the graph theory. Our results open a door for the understanding of domain patterns in topologically protected multiferroic systems. Disclination ; Topological defect ; Manganite ; Condensed matter physics ; Materials science ; Dislocation ; Hexagonal crystal system ; Domain (mathematical analysis) ; Topology (electrical circuits) ; Enhanced Data Rates for GSM Evolution ; Crystallographic defect ; Crystallography ; Physics ; Computer science ; Mathematics ; Liquid crystal ; Chemistry ; Combinatorics ; Artificial intelligence ; Ferromagnetism Multiferroics and related materials ; Ferroelectric and Piezoelectric Materials ; Photonic Crystals and Applications
Authors: Nouamane Laanait | Albina Y. Borisevich
Source: Microscopy and Microanalysis (article, 2018-08-01)
Field: Materials Science — Materials Chemistry

Deep Convolutional Neural Network Approach as a Universal Tool for Determination of Local 3D Structure from ABF STEM Images of Perovskitesy 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. Convolutional neural network ; Computer science ; Action (physics) ; Artificial intelligence ; Content (measure theory) ; Pattern recognition (psychology) ; Computer vision ; Mathematics ; Physics Electronic and Structural Properties of Oxides ; Magnetic and transport properties of perovskites and related materials ; Advanced X-ray and CT Imaging
Authors: Guilherme Duarte Ramos Matos | Gaetano Calabrò | David L. Mobley
Source: ChemRxiv (preprint, 2018-10-15)
Field: Materials Science — Materials Chemistry

Infinite Dilution Activity Coefficients as Constraints for Force Field Parameterization and Method Development Molecular simulations see widespread use in calculating various physical properties of interest, with a key goal being predictive molecular design. These simulations, including molecular dynamics (MD) simulations, begin with a underlying energy model or force field and then, based on this model, use simulations to compute properties of interest. However, one of the most significant challenges in molecular dynamics and modeling studies is ensuring that the force field is a good enough approximation of the underlying physics that computed quantities can be used to reproduce experimental properties with the desired level of accuracy. Parameterization of force fields depend on various experimental properties including as much of the chemistry of interest as possible. Physicochemical properties measurable in a relatively straightforward manner are particularly interesting for developers. Such properties can be measured for a relatively diverse chemical set and used to expand the parameterization dataset as needed. Here, we examine infinite dilution activity coefficients (IDACs) which are experimental quantities that can play this role. We retrieved 237 empirical IDACs from NIST's ThermoML, a database of measured thermodynamic properties, and we estimated the corresponding values using solvation free energy calculations. We found that calculated IDAC values correlate strongly with experiment. Specifically, the natural logarithm of calculated and experimental IDAC values shows a Pearson correlation coefficient of 0.85+/-0.02. The calculated IDAC values allow us to identify strengths and potential weaknesses of force field parameters for specific functional groups in solutes and solvents, suggesting these may be a valuable source of data for force field parameterization, capturing some of the same type of information as hydration and solvation free energies and thus potentially providing a useful new source of experimental data. Force field (fiction) ; Molecular dynamics ; Statistical physics ; Solvation ; Field (mathematics) ; Dilution ; Logarithm ; NIST ; Experimental data ; Thermodynamics ; Physics ; Computer science ; Chemistry ; Computational chemistry ; Mathematics ; Molecule ; Statistics ; Quantum mechanics ; Mathematical analysis Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Nicole Andree Mendoza
Source: eScholarship (California Digital Library) (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

Variable Selection and Spatial Models for Identifying Chemical Plumes in Hyperspectral Imagery Hyperspectral imaging is a remote sensing technique widely used in a variety of military and environmental applications. For example, hyperspectral images can be used to detect chemical plumes invisible to the human eye, and to identify their chemical structure. A hyperspectral image is a massive cube of data consisting of thousands of pixels each with dozens of observations over a range of frequencies in the electromagnetic spectrum. Algorithms that use hypothesis testing and assume independence over pixels have shown success in detecting gas clouds, but often fail in identifying chemical components. We approach identification problems in hyperspectral imaging as a variable selection problem, which can be solved robustly by taking advantage of spatial information in the image. For this purpose we develop Bayesian spatial model selection algorithms which use mixtures of g-priors, Gaussian Markov Random Fields, and Gaussian Process Priors to account for correlation among chemicals, to induce spatial dependence among pixels, and to account for nonlinearities in pixel signals. To illustrate the performance of the models we apply them to several partially synthesized hyperspectral images and show that our method outperforms state-of-the-art algorithms, such as the LASSO and Fused LASSO. Hyperspectral imaging ; Pixel ; Prior probability ; Computer science ; Artificial intelligence ; Data cube ; Pattern recognition (psychology) ; Spatial correlation ; Spatial analysis ; Gaussian process ; Gaussian ; Remote sensing ; Markov random field ; Bayesian probability ; Data mining ; Image (mathematics) ; Geography ; Image segmentation Spectroscopy and Chemometric Analyses ; Computational Drug Discovery Methods ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Alina Bruma | Canhui Wang | Wei‐Chang Yang | Dayne F. Swearer | Naomi J. Halas | Renu Sharma
Source: Microscopy and Microanalysis (article, 2018-08-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Combined Experimental and Theoretical Approach to Measure Spatially Resolved Local Surface Plasmon Resonances in Aluminum Nanocrystals 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. Nanocrystal ; Materials science ; Measure (data warehouse) ; Surface plasmon resonance ; Plasmon ; Aluminium ; Nanotechnology ; Surface plasmon ; Localized surface plasmon ; Surface (topology) ; Molecular physics ; Chemical physics ; Optoelectronics ; Nanoparticle ; Chemistry ; Composite material ; Geometry Gold and Silver Nanoparticles Synthesis and Applications ; Plasmonic and Surface Plasmon Research ; Advanced biosensing and bioanalysis techniques
Authors: Sharat Chidambaran | Amir Behjat | Souma Chowdhury
Source: arXiv (Cornell University) (preprint, 2018-07-20)
Field: Materials Science — Materials Chemistry

Multi-criteria Evolution of Neural Network Topologies: Balancing Experience and Performance in Autonomous Systems Majority of Artificial Neural Network (ANN) implementations in autonomous systems use a fixed/user-prescribed network topology, leading to sub-optimal performance and low portability. The existing neuro-evolution of augmenting topology or NEAT paradigm offers a powerful alternative by allowing the network topology and the connection weights to be simultaneously optimized through an evolutionary process. However, most NEAT implementations allow the consideration of only a single objective. There also persists the question of how to tractably introduce topological diversification that mitigates overfitting to training scenarios. To address these gaps, this paper develops a multi-objective neuro-evolution algorithm. While adopting the basic elements of NEAT, important modifications are made to the selection, speciation, and mutation processes. With the backdrop of small-robot path-planning applications, an experience-gain criterion is derived to encapsulate the amount of diverse local environment encountered by the system. This criterion facilitates the evolution of genes that support exploration, thereby seeking to generalize from a smaller set of mission scenarios than possible with performance maximization alone. The effectiveness of the single-objective (optimizing performance) and the multi-objective (optimizing performance and experience-gain) neuro-evolution approaches are evaluated on two different small-robot cases, with ANNs obtained by the multi-objective optimization observed to provide superior performance in unseen scenarios. Computer science ; Overfitting ; Network topology ; Implementation ; Distributed computing ; Maximization ; Software portability ; Artificial neural network ; Evolution strategy ; Artificial intelligence ; Evolutionary algorithm ; Topology (electrical circuits) ; Mathematical optimization ; Engineering ; Mathematics Machine Learning in Materials Science ; Advanced Neural Network Applications ; Advanced Memory and Neural Computing
Authors: Fariba Safaei | Shahla Khalili | Saied Nouri Khorasani | Laleh Ghasemi‐Mobarakeh | Rasoul Esmaeely Neisiany
Source: Journal of Polymer Science and Engineering (article, 2018-01-08)
Field: Chemistry — Organic Chemistry

Porogen effect of solvents on pore size distribution of solvent-casted polycaprolactone thin films In this study, the effect of porogenic solvents on pore size distribution of the polycaprolactone (PCL) thin films was investigated. Five thin PCL films were prepared using the solvent-casting method. Chloroform, Methylene Chloride (MC) and three different compositions of MC/ Dimethylformamide (DMF) (80/20, 50/50 and 20/80) were used as solvents. Scanning Electron Microscopy (SEM) investigations were employed to study morphology and consequently the pore size distribution of the prepared films. The PCL films made by chloroform and MC as a solvent were completely non-porous. Whereas the other films (made by a combination of MC and DMF) showed both uni-modal and bi-modal pore size distributions. Polycaprolactone ; Solvent ; Materials science ; Chemical engineering ; Thin film ; Composite material ; Chemistry ; Organic chemistry ; Nanotechnology ; Polymer ; Engineering Advanced Polymer Synthesis and Characterization