jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Huma Ajab | Asim Yaqub | Muhammad Shahid Nazir | Mohd Zul Helmi Rozaini | Mohd Azmuddin Abdullah
Source: BioResources (article, 2020-07-01)
Field: Chemistry — Electrochemistry

Optimization of oil palm-based cellulose and hydroxyapatite-carbon composite electrode for trace Pb(II) ions detection in aqueous system An electroanalytical technique was devised using oil palm-based cellulose and hydroxyapatite as modifiers to carbon electrodes for Pb(II) ions detection in an aqueous system. The cyclic voltammetry scan suggested increased active binding sites and faster electron transfer with quasi-reversible redox peaks with a larger anodic current peak and smaller oxidation potential values. The optimal conditions were attained using 10% modifier at pH 2 in 0.1 M HCl, −1.2 V deposition potential, 270 s deposition time, 25 Hz frequency, 0.020 V amplitude, rotation speed of 700 rpm, and the step potential of 0.005 V. The square wave anodic stripping voltammetry established at optimum level exhibited excellent selectivity and stability from 10 ppb to 100 ppb for Pb(II) ions detection. Sharp anodic peaks were observed at -0.48 V for Pb(II) ions with the detection limit of 0.095 ± 0.32 ppb and limit of quantitation of 0.32 ± 0.32 ppb. Detection limit ; Anodic stripping voltammetry ; Aqueous solution ; Analytical Chemistry (journal) ; Cyclic voltammetry ; Materials science ; Voltammetry ; Electrode ; Ion ; Stripping (fiber) ; Electrochemistry ; Inorganic chemistry ; Nuclear chemistry ; Chemistry ; Chromatography ; Physical chemistry ; Composite material ; Organic chemistry Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; Conducting polymers and applications
Authors: Saeed K. Kashani | Jacob E. Jessiman | Stephen G. Newman
Source: ChemRxiv (preprint, 2020-01-14)
Field: Chemistry — Organic Chemistry

Exploring Homogeneous Conditions for Mild Buchwald-Hartwig Amination in Batch and Flow We describe the use of high throughput experimentation to identify a number of conditions that enable Buchwald-Hartwig reactions to be carried out using readily available ligands (e.g. XantPhos) with DBU as a soluble, functional group tolerant, homogeneous base. Application of this system to diverse aminations in batch and flow are demonstrated, as is the translation of this technique to performing continuous Mizoroki-Heck and Sonogashira coupling reac-tions. Amination ; Sonogashira coupling ; Homogeneous ; Xantphos ; Chemistry ; Base (topology) ; Combinatorial chemistry ; Borylation ; Continuous flow ; Organic chemistry ; Palladium ; Catalysis ; Mathematics ; Biochemical engineering ; Engineering Catalytic Cross-Coupling Reactions ; Radical Photochemical Reactions
Authors: Yan Zhang | Ning Wang | Jingyi Li | Mohsen Mesbah | Kuan Yew Wong | Alireza Fallahpour | Bahman Nasiri‐Tabrizi | Jiangfei Yang
Source: Latin American Journal of Solids and Structures (article, 2020-01-01)
Field: Materials Science — Biomaterials

Mechanical properties modeling of severely plastically deformed biodegradable ZK60 magnesium alloy for bone implants The effectiveness of magnesium (Mg) alloys to improve the capability of bone tissue generation may be severely diminished if the required mechanical properties are not provided. Here, the effort is directed to model the mechanical performance of severely plastically deformed biodegradable ZK60 Mg alloy in bone regeneration protocols. For this purpose, the effects of parallel tubular channel angular pressing (PTCAP) on yield strength (σ YS ), ultimate tensile strength (σ UTS ), and elongation to failure (δ) were addressed. Given the multifaceted variables of the PTCAP with nonlinear interactions, a precise determination of the mechanical properties requires a large number of experiments. Therefore, gene expression programming (GEP) and genetic programming (GP) models were proposed to achieve appropriate combinations of mechanical properties for bone implant purposes based on a rational hypothesis that for correlation coefficient (|R|) higher than 0.8, a strong correlation is established between the predicted and measured values. The results verified that the highest mechanical performance was achieved at the second pass of PTCAP, thus has a great potential to be the most promising candidate for biodegradable implant material. Besides, the proposed models were capable of precisely predicting the mechanical performance of the SPD-processed biodegradable ZK60 Mg. Materials science ; Ultimate tensile strength ; Magnesium ; Elongation ; Magnesium alloy ; Pressing ; Alloy ; Gene expression programming ; Composite material ; Biomedical engineering ; Metallurgy ; Computer science ; Engineering Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; Titanium Alloys Microstructure and Properties
Authors: Hagen Eckert | Maria Montagna | Arezoo Dianat | Rafael Gutiérrez | M. Bobeth | Gianaurelio Cuniberti
Source: BMC Materials (article, 2020-06-16)
Field: Materials Science — Biomaterials

Exploring the organic–inorganic interface in biosilica: atomistic modeling of polyamine and silica precursors aggregation behavior Abstract Diatoms are a significant group of algae displaying a sizeable morphological diversity, whose underlying structure arises from nanopatterned silica. Extensive experimental evidence suggests that a delicate interplay between various organic components and polysilicic acid plays a crucial role in biosilica mineralization. Thus, gaining insight into the properties of this organic–inorganic interface is of great interest in understanding the mechanisms controlling biosilica formation over different length scales. In this work, we use all-atom Molecular Dynamics simulations to investigate the aggregation behavior of polysilicic acid and silica nanoparticles in solution in the presence of protonated long-chain polyamines with a focus on the nature of the driving forces mediating the organic–inorganic aggregation process. Our results show that electrostatic forces between organic and inorganic species are the dominant interaction responsible for largely preserving the structural integrity of the organic–inorganic aggregates in solution. Thus, aggregates involving electrically neutral polysilicic acid are fully dissolved in an aqueous environment, since hydrogen bonding and van der Waals interactions turn out to be not strong enough to keep the aggregates together. Our main simulation results are in qualitative agreement with in vitro experiments, so that we expect they can contribute to shedding light on the initial stages of biosilica mineralization in diatoms. Chemistry ; van der Waals force ; Mineralization (soil science) ; Chemical engineering ; Aqueous solution ; Hydrogen bond ; Protonation ; Nanoparticle ; Molecular dynamics ; Nanotechnology ; Chemical physics ; Molecule ; Organic chemistry ; Computational chemistry ; Materials science ; Nitrogen Diatoms and Algae Research ; Paleontology and Stratigraphy of Fossils ; Minerals Flotation and Separation Techniques
Authors: Phuoc Nguyen | Quang Hieu Vo | Ngoc Linh Le | SeokJin Eo | Lok-Won Kim
Source: Sensors (article, 2020-10-26)
Field: Materials Science — Materials Chemistry

An IoT Hardware Platform Architecture for Monitoring Power Grid Systems Based on Heterogeneous Multi-Sensors Partial discharge (PD) is a major indicator of various failures in power grid systems. PD exhibits a physical occurrence where a localized electrical discharge happens in insulation materials. This phenomenon causes damage to the insulating parts and, in various circumstances, leads to complete insulation breakdown. As a consequence, it can produce more costly outcomes such as abrupt outages or lost production. Therefore, PD detection plays a vital role in preventing insulation failure. In this work, we propose a system that utilizes heterogeneous sensors for the PD detection along with multi-sensor interface, real-time advanced denoise processing, flexible system operation, and Bluetooth-low-energy (BLE)-based ad hoc communication. Among the variety of heterogeneous sensors, several are developed by the application of nanomaterials and nanotechnology, thus outperforming the regular types. The proposed system successfully identifies the presence of PD from sensor signals using a microprocessor-based processing system and effectively performs an advanced denoising technique based on the wavelet transform through field-programmable-gate-array (FPGA)-based programmable logics. With the development of the system, we aim to achieve a solution with low cost, high flexibility and efficiency, and ease of deployment for the monitoring of power grid systems. Field-programmable gate array ; Embedded system ; Flexibility (engineering) ; Computer science ; Microprocessor ; Smart grid ; Electric power system ; Software deployment ; Grid ; Power (physics) ; Engineering ; Electrical engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Underwater Vehicles and Communication Systems
Authors: Sumita Karan | Bhanu Pratap | Shiv Pratap Singh Yadav | Fnu Ashish | Ajay K. Saxena
Source: Scientific Reports (article, 2020-11-30)
Field: Materials Science — Materials Chemistry

Structural and functional characterization of M. tuberculosis sedoheptulose- 7-phosphate isomerase, a critical enzyme involved in lipopolysaccharide biosynthetic pathway M. tuberculosis GmhA enzyme catalyzes the isomerization of D-sedoheptulose 7-phosphate into D-glycero-D-α-manno-heptose-7-phosphate in GDP-D-glycero-α-D-manno-heptose biosynthetic pathway. The D-glycero-α-D-manno-heptose is a major constituent of lipopolysaccharide and contributes to virulence and antibiotic resistance to mycobacteria. In current study, we have performed the structural and biochemical analysis of M. tuberculosis GmhA, the first enzyme involved in D-sedoheptulose 7-phosphate isomerization in GDP-D-α-D-heptose biosynthetic pathway. The MtbGmhA enzyme exits as tetramer and small angle X-ray scattering analysis also yielded tetrameric envelope in solution. The MtbGmhA enzyme binds to D-sedoheptulose 7-phosphate with K<sub>m</sub> ~ 0.31 ± 0.06 mM<sup>-1</sup> and coverts it to D-glycero-D-α-manno-heptose-7-phosphate with catalytic efficiency (k<sub>cat</sub>/K<sub>m</sub>) ~ 1.45 mM<sup>-1</sup> s<sup>-1</sup>. The residues involved in D-sedoheptulose 7-phosphate and Zn<sup>2+</sup> binding were identified using modeled MtbGmhA + D-sedoheptulose 7-phosphate + Zn<sup>2+</sup> structure. To understand the role in catalysis, six site directed mutants of MtbGmhA were generated, which showed significant decrease in catalytic activity. The circular dichroism analysis showed ~ 46% α-helix, ~ 19% β-sheet and ~ 35% random coil structures of MtbGmhA enzyme and melting temperature ~ 53.5 °C. Small angle X-ray scattering analysis showed the tetrameric envelope, which fitted well with modeled MtbGmhA tetramer in closed conformation. The MtbGmhA dynamics involved in D-sedoheptulose 7-phosphate and Zn<sup>2+</sup> binding was identified using dynamics simulation and showed enhanced stability in presence of these ligands. Our biochemical data and structural knowledge have provided insight into mechanism of action of MtbGmhA enzyme, which can be targeted for novel antibiotics development against M. tuberculosis. Heptose ; Isomerase ; Enzyme ; Biochemistry ; Triosephosphate isomerase ; Tetramer ; Cell envelope ; Stereochemistry ; Biosynthesis ; Chemistry ; Circular dichroism ; Phosphofructokinase 2 ; Biology ; Mutant ; Escherichia coli Enzyme Structure and Function ; Bacterial Genetics and Biotechnology ; Amino Acid Enzymes and Metabolism
Authors: Ming‐Der Jean | Chengwu Liu | Pao-Hua Yang | Wen‐Hsien Ho
Source: Materials Science (article, 2020-03-17)
Field: Materials Science — Materials Chemistry

Optimization of Wear Behavior of DLC Coatings Through Optimization of Deposition Conditions Based on genetic algorithm (GA) and fuzzy neural network, a new method for the study of sputtering process is proposed in this paper. Diamond-like carbon (DLC) coatings were deposited on SKD11 steel by magnetron sputtering. An orthogonal array design is implemented and the effects of control factors on surface properties of the coatings were systematically analyzed. The coating properties were investigated by scanning electron microscopy and Raman spectroscopy, and wear volume surface performance of the Zr-doped DLC coatings was evaluated by a wear tests pin-on-disk tribometer. The Raman analyses showed that, at lower ID/IG ratio, a lower wear volume of the Zr-doped DLC coatings can be obtained. Scratch tests as well as Rockwell indentation tests revealed that the graded Zr-doped DLC structures efficiently provide better adhesive strength of DLC coatings. The results show that the wear behaviors of the DLC coatings can be improved by Zr-doping, which the Zr-doped DLC coatings exhibited promising tribological properties. Also, the predictive ability of the GA-ANFIS computations for the tribological behaviors of the Zr-DLC coatings within the experimental domains proved to be reliably obtained, where the forecasted values and experimental results are close. Materials science ; Tribometer ; Tribology ; Sputter deposition ; Diamond-like carbon ; Raman spectroscopy ; Coating ; Composite material ; Scanning electron microscope ; Scratch ; Doping ; Sputtering ; Thin film ; Nanotechnology ; Optoelectronics Diamond and Carbon-based Materials Research ; Metal and Thin Film Mechanics ; Lubricants and Their Additives
Authors: Shunyang Wang | Tobias Kind | Dean J. Tantillo | Oliver Fiehn
Source: Research Square (preprint, 2020-08-04)
Field: Chemistry — Spectroscopy

Predicting in-silico electron ionization mass spectra using quantum chemistry Abstract Compound identification by mass spectrometry needs reference mass spectra. While there are over 102 million compounds in PubChem, less than 300,000 curated electron ionization (EI) mass spectra are available from NIST or MoNA mass spectral databases. Here, we test quantum chemistry methods (QCEIMS) to generate in-silico EI mass spectra (MS) by combining molecular dynamics (MD) with statistical methods. To test the accuracy of predictions, in-silico mass spectra of 451 small molecules were generated and compared to experimental spectra from the NIST 17 mass spectral library. The compounds covered 43 chemical classes, ranging up to 358 Da. Organic oxygen compounds had a lower matching accuracy, while computation time exponentially increased with molecular size. The parameter space was probed to increase prediction accuracy including initial temperatures, the number of MD trajectories and impact excess energy (IEE). Conformational flexibility was not correlated to the accuracy of predictions. Overall, QCEIMS can predict 70 eV electron ionization spectra of chemicals from first principles. Improved methods to calculate potential energy surfaces (PES) are still needed before QCEIMS mass spectra of novel molecules can be generated at large scale. In silico ; Mass spectrum ; Chemistry ; Ionization ; Quantum chemistry ; Spectral line ; Electron ; Chemical physics ; Mass spectrometry ; Quantum ; Computational chemistry ; Atomic physics ; Ion ; Physics ; Quantum mechanics ; Chromatography ; Organic chemistry ; Reaction mechanism ; Biochemistry ; Catalysis Mass Spectrometry Techniques and Applications ; Ion-surface interactions and analysis ; X-ray Spectroscopy and Fluorescence Analysis
Authors: Mikhail Y. Shalaginov | Sensong An | Yifei Zhang | Fan Yang | Peter Su | Vladimir Liberman | Jeffrey B. Chou | Christopher Roberts | Myungkoo Kang | Carlos Rı́os | Qingyang Du | Clayton Fowler | Anu Agarwal | Kathleen Richardson | Clara Rivero‐Baleine | Hualiang Zhang | Juejun Hu | Tian Gu
Source:  (article, 2020-08-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Reconfigurable all-dielectric metalens based on phase change materials Optical metasurfaces, planar sub-wavelength nano-antenna arrays with the singular ability to sculpt wave front in almost arbitrary manners, are poised to become a powerful tool enabling compact and high-performance optics with novel functionalities. A particularly intriguing research direction within this field is active metasurfaces, whose optical response can be dynamically tuned post-fabrication, thus allowing a plurality of applications unattainable with traditional bulk optics. The efforts to date, however, still face major performance limitations in tuning range, optical quality, and efficiency especially for non-mechanical actuation mechanisms. In this paper, we introduce an active metasurface platform combining phase tuning covering the full 2&pi; range and diffraction-limited performance using an all-dielectric, low-loss architecture based on optical phase change materials (O-PCMs). We present a generic design principle enabling binary switching of metasurfaces between arbitrary phase profiles. We implement the approach to realize a high-performance varifocal metalens. The metalens is constructed using Ge<sub>2</sub>Sb<sub>2</sub>Se<sub>4</sub>Te<sub>1</sub> (GSST), an O-PCM with a large refractive index contrast and unique broadband low-loss characteristics in both amorphous and crystalline states. The reconfigurable metalens features focusing efficiencies above 20% at both states for linearly polarized light and a record large switching contrast ratio (CR) close to 30 dB. We further validate aberration-free and multi-depth imaging using the metalens, which represents the first experimental demonstration of a non-mechanical active metalens with diffraction-limited performance. Materials science ; Optics ; Dielectric ; Refractive index ; Optoelectronics ; Diffraction ; Phase (matter) ; Fabrication ; Broadband ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Plasmonic and Surface Plasmon Research
Authors: Shi Jin | Lei Li | Zhenli Xu | Yue Zhao
Source: arXiv (Cornell University) (preprint, 2020-10-04)
Field: Chemistry — Physical and Theoretical Chemistry

A random batch Ewald method for particle systems with Coulomb interactions We develop a random batch Ewald (RBE) method for molecular dynamics simulations of particle systems with long-range Coulomb interactions, which achieves an $O(N)$ complexity in each step of simulating the $N$-body systems. The RBE method is based on the Ewald splitting for the Coulomb kernel with a random "mini-batch" type technique introduced to speed up the summation of the Fourier series for the long-range part of the splitting. Importance sampling is employed to reduce the induced force variance by taking advantage of the fast decay property of the Fourier coefficients. The stochastic approximation is unbiased with controlled variance. Analysis for bounded force fields gives some theoretic support of the method. Simulations of two typical problems of charged systems are presented to illustrate the accuracy and efficiency of the RBE method in comparison to the results from the Debye-Hückel theory and the classical Ewald summation, demonstrating that the proposed method has the attractiveness of being easy to implement with the linear scaling and is promising for many practical applications. Ewald summation ; Coulomb ; Statistical physics ; Fourier series ; Range (aeronautics) ; Monte Carlo method ; Scaling ; Kernel (algebra) ; Fourier transform ; Stochastic process ; Physics ; Applied mathematics ; Molecular dynamics ; Mathematics ; Mathematical analysis ; Quantum mechanics ; Materials science Electrostatics and Colloid Interactions ; Theoretical and Computational Physics ; Spectroscopy and Quantum Chemical Studies
Authors: Xiaolong Sun | Zhisheng Liu | Xiao Qin | Dongfang Zeng | Yingmei Yin
Source: Frontiers in Materials (article, 2020-07-28)
Field: Materials Science — Materials Chemistry

Purifying Effect Evaluation of Pavement Surfacing Materials Modified by Novel Modifying Agent Functional pavement material with exhaust-purifying performance has been focused gradually in recent years. For improving the purifying effect of functional micro surfacing, two types of raw ore powders with exhaust-purifying potentials were selected as novel functional modifiers. Firstly, the road performance of purifying micro surfacing was evaluated according to the ASTM and ISSA standards. Then, the dispersion state of modifying agent in emulsified asphalt evaporation residue was analyzed and discussed through using SEM and FTIR. Finally, the purifying effect of micro surfacing on exhaust was examined in laboratory to investigate the impact of various experimental conditions on purifying performance. Meanwhile, the purifying performance was also monitored in field test. The results showed that road performance of purifying micro surfacing could fulfill the requirements of relevant technical standards. Pyrite had better dispersion property than specularite and titanium dioxide inside asphalt. The purifying micro surfacing could achieve better purifying effect on NOx and COx than traditional micro surfacing with TiO2. These environmental-friendly pavement materials would provide new solutions for the reduction in polluting emissions of automobile exhausts. Asphalt ; Materials science ; Raw material ; Pyrite ; Environmental science ; Waste management ; Composite material ; Metallurgy ; Chemistry ; Engineering Catalytic Processes in Materials Science ; Industrial Gas Emission Control ; Thermal and Kinetic Analysis
Authors: Felix Pütz | Manuel Henrich | Niklas Fehlemann | Andreas Roth | Sebastian Münstermann
Source: Preprints.org (preprint, 2020-06-05)
Field: Materials Science — Materials Chemistry

Generating Input Data for Microstructure Modelling: A Deep Learning Approach Using Generative Adversarial Networks For the generation of representative volume elements a statistical description of the relevant parameters is necessary. These parameters usually describe the geometric structure of a single grain. Commonly, parameters like area, aspect ratio and slope of the grain relative to the rolling direction are applied. However, usually simple distribution functions like log normal or gamma distribution are used. Yet, these do not take the interdependencies between the microstructural parameters into account. To fully describe any metallic microstructure though, these interdependencies between the singular parameters need to be accounted for. To accomplish this representation, a machine learning approach was applied in this study. By implementing a Wasserstein generative adversarial network, the distribution, as well as the interdependencies could accurately be described. A validation scheme was applied to verify the excellent match between microstructure input data and synthetically generated output data. Representation (politics) ; Interdependence ; Generative grammar ; Computer science ; Adversarial system ; Artificial neural network ; Artificial intelligence ; Algorithm Machine Learning in Materials Science ; Injection Molding Process and Properties ; Manufacturing Process and Optimization