jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kanchan Chauhan | Vishnu P. Choudhari
Source: International Journal of ChemTech Research (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

Stability indicating HPTLC Method Development and Validation for Estimation of Glucosamine and Diacerein as Bulk Drug and in Drug Formulation by Derivatization The objective of the method was to develop and validate a sensitive stability indicating high performance thin layer chromatographic (HPTLC) method for simultaneous estimation of glucosamine and diacerein. The chromatographic separation was done on aluminum plates precoated with silica gel 60F 254 using n-butanol: Water: Glacial Acetic Acid (7:1.5:1.5 v/v/v) as mobile phase. Developed plates were scanned at 254 nm for spot of diacerein followed by derivatization with ninhydrin reagent by heating at 110 0 C for 5 min in a preheated oven and scanned at 366 nm for spot of glucosamine. The retention factor for glucosamine and diacerein were found to be 0.23 and 0.81, respectively. Validation of the proposed method was carried out according to International Conference on Harmonization (ICH) guidelines. The current method demonstrates good linearity with correlation coefficients values 0.9996 and 0.9995 for glucosamine and diacerein, respectively. The method was validated for different parameters like precision, recovery and robustness and the values obtained were within ICH limits. For forced degradation studies the drugs were subjected to oxidation, acid and base hydrolysis, dry heat and UV light as per ICH guidelines. Forced degradation studies indicated the suitability of the method for stability studies. Since the method effectively separates the drug from its degradation products it could be used as stability indicating method for analysis of individual drugs and the combined dosage form. Derivatization ; Chromatography ; Drug ; Chemistry ; Glucosamine ; Pharmacology ; Medicine ; High-performance liquid chromatography ; Organic chemistry Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Chromatography ; Natural Antidiabetic Agents Studies
Authors: Matteo Zanda
Source: Synlett (article, 2018-12-14)
Field: Chemistry — Organic Chemistry

SYNFORM ISSUE 2019/01 First of all, Happy New Year! At the beginning of every year there is a "trend" going on in magazines, newspapers and the online marketing community: asking a number of experts about the upcoming trends in the New Year and beyond. As these articles are very popular, we thought we could apply the same concept to our beloved field of chemistry and ask our Editors for their opinion on the hottest trends or topics in organic synthesis. Answers from a few of us can be found in the first article of this year. Chemistry ; Earth science ; Geology Catalytic Cross-Coupling Reactions ; Catalytic C–H Functionalization Methods ; Asymmetric Hydrogenation and Catalysis
Authors: Tao Tao Qiang | Honghong Gao
Source: arXiv (Cornell University) (preprint, 2018-04-23)
Field: Materials Science — Materials Chemistry

Materials science and engineering: New vision in the era of artificial intelligence Scientific discovery evolves from the experimental, through the theoretical and computational, to the current data-intensive paradigm. Materials science is no exception, especially for computational materials science. In recent years, great achievements have been made in the field of materials science and engineering (MSE). Here, we review the previous paradigms of materials science and some classical MSE models. Then, our data-intensive MSE (DIMSE) model is proposed to reshape future materials innovations. This work will help to address the global challenge for materials discovery in the era of artificial intelligence (AI), and essentially contribute to accelerating future materials continuum. Artificial intelligence ; Science and engineering ; Artificial vision ; Engineering ethics ; Engineering ; Computer science ; Cognitive science ; Psychology Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; X-ray Diffraction in Crystallography
Authors: Song Seonja | Jang Changkook | Kyeongho Shin | Ju-Hyung Kim | Young-Seok Kim | Chu Jaeuk
Source:  (article, 2018-05-01)
Field: Materials Science — Materials Chemistry

Synthesis of Thermal Compound and Its Application as a Thermal Interface Material of Power Module The development and growth of highly integrated semiconductors is being used for high-performance mobile phones, large-capacity computer servers, and Artificial Intelligence for high-speed computation processing. This technology development requires advanced technology of basic semiconductor packaging. In realizing such technology, thermal analysis and development of excellent heat dissipation materials are very essential for the use of products. We have developed a heat dissipation compound using a high thermal material such as Al <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> and ZnO and reliable polymer resins. We also confirmed the theoretical foundation of the heattransfer effect by computer simulation and applied it to the model of the SiC power module in Electric/Hybrid Electric Vehicle to see its efficiency improve. Junction temperature ; Computer science ; Thermal ; Dissipation ; Server ; Electrical engineering ; Engineering ; Physics ; Computer network ; Thermodynamics Thermal properties of materials ; Heat Transfer and Optimization ; Electronic Packaging and Soldering Technologies
Authors: Xiuwen Zhang | Jian‐Bai Xia
Source: Journal of Semiconductors (article, 2018-07-01)
Field: Materials Science — Materials Chemistry

Approaches to design inorganic semiconductors while maintaining structural motifs Inorganic semiconductors are the essential constituents of information society, having enabled most of the devices for microelectronics, optoelectronics, new energy technology, healthcare devices, artificial intelligence, etc. From the view of condensed matter physics and materials science, inorganic semiconductors are not intricate. However, this special class of materials are keeping inspiring new inventions and consequently new technologies, which in turn promote the design of new semiconductors. The kinds of semiconductors in nature are finite. On one hand, the new techniques need semiconductors with better properties than existing ones, on the other hand, the new computers’ software and hardware develop so rapid that it is possible to design new semiconductors according to people’s desire before manufacturing them. In this paper, we review the rational design of inorganic semiconductors by transformation of their elemental constituents, while maintaining their structure motifs. Semiconductor ; Materials science ; Nanotechnology ; Optoelectronics Quantum Dots Synthesis And Properties ; Electronic and Structural Properties of Oxides ; Chalcogenide Semiconductor Thin Films
Authors: Ye Yuan | Tian Bo-Bo | Chun‐Gang Duan
Source: Acta Physica Sinica (article, 2018-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Theoretical study on magnetoelectric effect in multiferroic tetragonal BiMnO3 Perovskite BiMnO3 with ferroelectric and ferromagnetic ordering simultaneously, as a kind of multiferroics, can be expected to have the coupling between the magnetic and dielectric properties as well as their control by the application of electric fields. This advantage can make BiMnO3 a good candidate for an artificial synapse material. Under the framework of the density functional theory, in this paper we adopt the generalized gradient approximation (GGA+U) plane wave pseudopotential method to calculate the ferroelectricity double-well potential curves and magnetic moments of Mn of tetragonal BiMnO3, with 0.18% and 4% strain exerted in its x-y plane. The results show that the magnetic moment of Mn monotonically increases from paraelectric state to ferroelectric state. It means that the ferromagnetic property of tetragonal BiMnO3 can be controlled by the intensity of polarization. The greater the stress, the greater the range of magnetic moment is. This would imply that the multiferroic artificial synapse device based on BiMnO3 can bring another degree of freedom into designing the complex cognitive systems of artificial intelligence in the future. Ferroelectricity ; Condensed matter physics ; Multiferroics ; Tetragonal crystal system ; Magnetic moment ; Materials science ; Ferromagnetism ; Dielectric ; Physics ; Quantum mechanics ; Optoelectronics Multiferroics and related materials
Authors: Guangyu Liu | Kaikai Xu | Qi Yu | Yang Liu
Source: Scientia Sinica Informationis (article, 2018-05-08)
Field: Materials Science — Polymers and Plastics

Advances in electronic skin research Skin is the body's largest organ, and can feel thetemperature, humidity, pressure, and external complex stimuli. Recreatingthe properties of human skin through an electronic system (electronic skin)is a hot topic in research with a wide range of applications in artificialintelligence, robots, and man–machine interfaces. In order to mimic humanskin's sense of touch, researchers use different transmission mechanisms and structuraldesigns to develop a flexible, stretchable, high-sensitivity, and high-resolution sensor array. High-density flexible circuit integrationtechnology, wireless technology, and self-powered technology make theelectronic skin portable and removable. Self-healing technology enables theelectronic skin to be repaired from accidental scratching to compensate fordevice function. This review mainly covers the latest domestic and foreignmaterials, devices, and advanced technologies used to improve the performanceof electronic skin to imitate the perception of skin and generate bionicsignals. Dermatology ; Medicine Synthesis and properties of polymers
Authors: Pratik Vangal | Pamela Svenson
Source: Journal of Emerging Investigators (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Examining Heat Recovery from Electric Light Bulbs Using Thermoelectric Generators In 2015, the US consumed about 400 billion kilowatt- hours (kWh) of electricity for lighting. According to the US Environmental Protection Agency (EPA), one third of the US energy consumption is wasted as heat. Light (solar) and vibration (piezoelectric) are common energy harvesting sources. Thermoelectric generators (TEGs), based on the Seebeck effect, have the capability to generate electricity from temperature differences. This study evaluates the feasibility of using TEGs by utilizing the thermal gradient of a household light bulb with ambient air as a viable source of energy. Initial results using TEGs with a Light Emitting Diode (LED) bulb shows up to 0.9 mW of harvestable energy. The experiments show that a better heat-sink enhanced setup can maximize the thermal gradient across both sides of the TEG, resulting in a ninefold increase in the energy efficiency to 8.3 mW. Finally, a 3D-printed TEG model, custom designed to fit conventional electric bulbs, demonstrates the promise of the proposed solution. Every bit of energy-recycling matters. The impact of using TEG-enabled light bulbs throughout millions of households will greatly benefit the lives of many by encouraging energy recycling and reducing the amount of fossil fuels being consumed. Electricity ; Incandescent light bulb ; Thermoelectric effect ; Thermoelectric generator ; Automotive engineering ; Environmental science ; Electric potential energy ; Light-emitting diode ; Thermal energy ; Energy harvesting ; Energy consumption ; Materials science ; Electricity generation ; Energy recovery ; Heat sink ; Electrical engineering ; Energy (signal processing) ; Optoelectronics ; Power (physics) ; Engineering Advanced Thermoelectric Materials and Devices ; Building Energy and Comfort Optimization ; Innovative Energy Harvesting Technologies
Authors: J. Krawczyk | E. Różniata | S. Zimowski | M. Kot | R. Dądrowski | R. Dziurka | Łukasz Frocisz
Source: Archives of Metallurgy and Materials (article, 2018-06-30)
Field: Materials Science — Materials Chemistry

The Role of Microstructure in High Temperature Tribology of Iron Alloys The present paper describe the issue of tool materials wear in a high temperature conditions. The investigations were performed at the cast steel tool material at the tribological contact to the structural steel. The investigations aim was to determine the role of microstructure in a tribological properties between the structural steel and tool material. The results of such investigation could be referenced to the industry conditions and could answer about the problems of tool materials wear. The observations of the wear mechanisms were referred to the microstructure of the mill rolls. The laboratory tests ware aimed at evaluating the thermal treatment modification effect on the cast steels properties. A significant role of the morphology of ledeburitic cementite and secondary cementite on the tribological properties was exhibited. The investigations assumed the presence of an austenitic matrix with primary and secondary cementite. Influence of varying morphology carbides was described. in the cast steel microstructure. The investigation results make possible to point to a direction of carbide morphology change with the purpose of obtaining the assumed properties of hot operation tools. Cementite ; Microstructure ; Tribology ; Materials science ; Metallurgy ; Carbide ; Ledeburite ; Austenite ; Cast iron ; Structural material Metal Alloys Wear and Properties ; Advanced materials and composites ; Tribology and Wear Analysis
Authors: T. M. Finch | Casey S. Greene | Jennifer Loros | Jay Dunlap
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-04-14)
Field: Chemistry — Spectroscopy

Learning and Imputation for Mass-spec Bias Reduction (LIMBR) Abstract Motivation Decreasing costs are making it feasible to perform time series proteomics and genomics experiments with more replicates and higher resolution than ever before. With more replicates and time points, proteome and genome-wide patterns of expression are more readily discernible. These larger experiments require more batches exacerbating batch effects and increasing the number of bias trends. In the case of proteomics, where methods frequently result in missing data this increasing scale is also decreasing the number of peptides observed in all samples. The sources of batch effects and missing data are incompletely understood necessitating novel techniques. Results Here we show that by exploiting the structure of time series experiments, it is possible to accurately and reproducibly model and remove batch effects. We implement Learning and Imputation for Mass-spec Bias Reduction (LIMBR) software, which builds on previous block based models of batch effects and includes features specific to time series and circadian studies. To aid in the analysis of time series proteomics experiments, which are often plagued with missing data points, we also integrate an imputation system. By building LIMBR for imputation and time series tailored bias modeling into one straightforward software package, we expect that the quality and ease of large-scale proteomics and genomics time series experiments will be significantly increased. Contact alexander.m.crowell@gmail.com , jay.c.dunlap@dartmouth.edu Imputation (statistics) ; Missing data ; Computer science ; Software ; Proteomics ; Data mining ; Time series ; Artificial intelligence ; Machine learning ; Biology Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Gene expression and cancer classification
Authors: Anand Dixit
Source: Iowa State University Digital Repository (Iowa State University) (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Developments in MCMC diagnostics and sparse Bayesian learning models This dissertation consists of three research articles on the topic of Markov chain Monte Carlo (MCMC) diagnostics and sparse Bayesian learning models. The first article consists of MCMC diagnostic tools based on Kullback Leibler (KL) divergence and smoothing methods. These tools can assess the joint convergence of multiple variables and detect non convergence when MCMC chains get stuck at a particular mode of a multi modal stationary distribution. Further, in case of non convergence of multiple MCMC chains, the visualization tool can be used to investigate reasons for non convergence. The second article deals with assessing posterior propriety of some sparse Bayesian learning models. Relevance Vector Machine (RVM) is a popular sparse Bayesian learning model that assumes improper prior over its hyperparameters. We prove that this improper prior leads to an improper posterior. Further, we also provide necessary and sufficient conditions for posterior propriety of RVM. Additionally, we also prove the posterior impropriety of some Bayesian learning models that have a prior structure similar to that of RVM. In the third article, we propose to replace multiple penalties of RVM with a single penalty. The new model is named as single penalty relevance vector machine (SPRVM) and is analyzed using a semi Bayesian approach. The SPRVM allows for computation of Monte Carlo standard errors since we prove the geometric ergodicity of its associated Gibbs sampler. Such a Monte Carlo standard error cannot be computed in the case of RVM since the rate of convergence of its associated Gibbs sampler is not known. Thus, through these three articles we hope to make valuable additions to the literature of MCMC diagnostics and sparse Bayesian learning models. Markov chain Monte Carlo ; Bayesian probability ; Artificial intelligence ; Computer science ; Bayesian inference ; Machine learning Machine Learning in Materials Science
Authors: Shubham Gupta | Sara Ahadi | Wenyu Zhou | Hannes Röst
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-10-10)
Field: Chemistry — Spectroscopy

DIAlignR provides precise retention time alignment across distant runs in DIA and targeted proteomics Abstract SWATH-MS has been widely used for proteomics analysis given its high-throughput and reproducibility but ensuring consistent quantification of analytes across large-scale studies of heterogeneous samples such as human-plasma remains challenging. Heterogeneity in large-scale studies can be caused by large time intervals between data-acquisition, acquisition by different operators or instruments, intermittent repair or replacement of parts, such as the liquid chromatography column, all of which affect retention time (RT) reproducibility and successively performance of SWATH-MS data analysis. Here, we present a novel algorithm for retention time alignment of SWATH-MS data based on direct alignment of raw MS2 chromatograms using a hybrid dynamic programming approach. The algorithm does not impose a chronological order of elution and allows for alignment of elution-order swapped peaks. Furthermore, allowing RT-mapping in a certain window around coarse global fit makes it robust against noise. On a manually validated dataset, this strategy outperforms the current state-of-the-art approaches. In addition, on a real-world clinical data, our approach outperforms global alignment methods by mapping 98% of peaks compared to 67% cumulatively and DIAlignR can reduce alignment error up to 30-fold for extremely distant runs. The robustness of technical parameters used in this pairwise alignment strategy has also been demonstrated. The source code is released under the BSD license at https://github.com/Roestlab/DIAlignR . Abbreviations: AUC Area Under the Curve DIA Data-independent acquisition LC Liquid chromatography LOESS Local weighted regression RSE Residual Standard Error RT Retention time XIC Extracted ion chromatograms Data Availability: Raw chromatograms and features extracted by OpenSWATH are available on PeptideAtlas. Servername: ftp.peptideatlas.org Username: PASS01280 Password: KQ2592b Robustness (evolution) ; Residual ; Computer science ; Elution ; Pairwise comparison ; Artificial intelligence ; Algorithm ; Chromatography ; Chemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: H. Jansen | P. Schuetze
Source:  (article, 2018-12-05)
Field: Materials Science — Surfaces, Coatings and Films

Simulation of material budget measurements with beam telescopes High-precision particle tracking devices allow for a two-dimensional analysis of the material budget distribution of, e.g., particle detectors and their periphery. These tracking devices, called beam telescopes, enable a precise measurement of the trajectory of charged particles with a position resolution of a few micrometer and an angular resolution of the order of a few ten microradian. In this contribution, the material budget of a structured aluminium cube is reconstructed from various estimators based on the deflection angles of simulated electron trajectories. Probing a target under various rotation angles enables a tomographic reconstruction of the target. We discuss the performance of width estimators of the scattering angle distributions and their impact on the contrast and the resolution of the reconstructed two- and three-dimensional images. At a voxel size of 0.1 mm $\times$ 0.1 mm $\times$ 0.1 mm, we reconstruct the material budget with a contrast to noise ratio of $5.6\pm0.2$ and an edge resolution of about $(70\pm10)$ micrometre. Optics ; Angular resolution (graph drawing) ; Physics ; Cube (algebra) ; Image resolution ; Tracking (education) ; Detector ; Deflection (physics) ; Scattering ; Geometry Electron and X-Ray Spectroscopy Techniques ; Advanced X-ray Imaging Techniques ; Advancements in Photolithography Techniques
Authors: Megan Miller | Chung-Hsuan Huang | Tariq Akmal | Ryan Anderson | Phillip A. Himmer
Source:  (article, 2018-05-10)
Field: Materials Science — Surfaces, Coatings and Films

Fluidic channels in the classroom: Fabrication and integration in fluid mechanics is currently Microfluidics Scientist and Lithography Specialist at Montana Microelectromechanical systems ; Fabrication ; Fluidics ; Microfluidics ; Microsystem ; Nanotechnology ; Materials science ; Mechanical engineering ; Photolithography ; Microfabrication ; Epoxy ; Computer science ; Engineering ; Electrical engineering ; Composite material Surface Modification and Superhydrophobicity ; Plasma Diagnostics and Applications ; Experimental Learning in Engineering
Authors: Bastien Durand | Ahmed Zouari | Han Zhao
Source:  (preprint, 2018-05-24)
Field: Materials Science — Materials Chemistry

Biaxial Compression Tests on Hopkinson Bars A biaxial compression Hopkinson bar set-up bas been designed. It consists in a projectile, an input bar and two co-axial output bars. After the projectile impact on the input bar, the internal output bar measures the axial loading of the cross sample whereas the external output bar measures its transversal loading via a mechanism with sliding surfaces. Gauges glued on the bars enable stain measurements which lead to the forces and to the displacements on the interfaces between the bars and the mounting. The displacement field of the sample is obtained by high-speed imaging and by digital image correlation. Experiments show that the set-up works despites two disadvantages. Firstly, the transversal force in the sample is over-estimated because of the friction in the mechanism. Moreover, comparisons between the displacements on the bars interfaces and the sample displacement field display that the clearance have an influence on the sample loading. Compression (physics) ; Materials science ; Split-Hopkinson pressure bar ; Compression test ; Dynamic range compression ; Structural engineering ; Composite material ; Engineering ; Strain rate High-Velocity Impact and Material Behavior ; Electromagnetic Launch and Propulsion Technology ; Optical measurement and interference techniques