jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kenechi Nwosu‐Obieogu
Source: Gazi University Journal of Science Part A Engineering and Innovation (article, 2021-12-30)
Field: Chemistry — Analytical Chemistry

Artificial Neural Network Predictive Modelling of luffa cylindrica Seed Oil Antioxidant Yield This study applied artificial neural network (ANN) in evaluating the models for terpineol and polyphenol yield from luffa cylindrica seed oil. The experiment was carried out at a temperature (60-80oC), time (4-6 hours), and solvent/seed ratio (8-12 ml/g) with response as antioxidant yield. FTIR (Fourier Transform Infra-red Spectroscopy) revealed the presence of terpineol and polyphenol at peaks of 1461.1cm-1 and 3008.0cm-1 respectively. The ANN prediction indices are thus; terpineol (R2= 9.9999E-1, MSE=2.25766E-9) and polyphenol (R2=9.9999E-1, MSE=4.42588E-10). This study reveals that the ANN technique can successfully predict antioxidants from luffa cylindrica seed oil. Polyphenol ; Yield (engineering) ; Antioxidant ; Fourier transform infrared spectroscopy ; Chemistry ; Food science ; Botany ; Horticulture ; Biology ; Organic chemistry ; Materials science ; Engineering ; Chemical engineering Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Edible Oils Quality and Analysis
Authors: Rebaz Anwar Omer | Lana Omer Ahmed | Jwameer HAMA | Pelin Koparır
Source: El-Cezeri Fen ve Mühendislik Dergisi (article, 2021-11-19)
Field: Chemistry — Organic Chemistry

Structural Analysis of Epinephrine by Combination of Density Functional Theory and Hartree-Fock Methods In this study, we built a model to predict the structure and chemical properties of epinephrine using Density Functional Theory (DFT) and Hartree-Fock (HF) methods, as the methods currently playing a significant role in in computational quantum theories. In the model, six basis sets of DFT and HF methods were used to calculate bandgap energies, which the basis set 6-311++G found to be optimal set, as the difference between the methods were minimum. The basis set 6-311++G was further used to characterize the most stable molecular geometry of epinephrine, as well as the molecular characteristics. Then, the basis set B3LYP/6-31G(d,p) applied on epinephrine to investigate the energy of the highest occupied molecular orbital (EHOMO), the energy of the lowest unoccupied molecular orbital (ELUMO), energy gap (ΔE = ELUMO - EHOMO) and the dipole moment (μ). The fraction of transferred electrons (ΔN) was also calculated, which determined the interaction between the iron surface and epinephrine compound. Corrosion inhibitor behavior can therefore be predicted from the calculated data without an experimental study. The findings of the calculations show good relation between organic-based corrosion inhibitors and quantum chemical parameters process. The parametrization and stimulation optimized in this study can be used as a model to predict the chemical structure and activity of any compound with known chemical formula. Basis set ; Density functional theory ; Dipole ; Computational chemistry ; Chemistry ; Band gap ; Hartree–Fock method ; Molecular orbital ; Hybrid functional ; Ab initio ; Molecule ; Thermodynamics ; Molecular physics ; Physical chemistry ; Quantum mechanics ; Physics ; Organic chemistry Inorganic and Organometallic Chemistry ; Nonlinear Optical Materials Research ; Advanced Chemical Physics Studies
Authors: Jiyao Wang | Ling Qin | Wei Xu
Source: Communications Materials (article, 2021-09-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Flexible and high precision thermal metasurface Abstract Thermal metamaterials are artificial materials used to manipulate heat flow in many applications, such as thermal protection, thermal camouflage, and precise temperature control. Most of the existing thermal metamaterials are mainly based on metal, which makes their fabrication complex and time-consuming, and limits their flexibility. Here, we show a strategy to simplify the fabrication process, improve machining accuracy, and realize flexibility in thermal metasurfaces. Our proposed thermal metasurface is fabricated by laser engraving of copper-graphene coating surface, utilizing graphene coating with high thermal conductivity instead of the traditional filling materials of low thermal conductivity. It maintains the integrity of copper substrate, giving the metasurface a good heat dispersion. Controlled temperature gradient patterns are established, and the metasurface can be bent without changing its features, except for a slight variation in its thermal gradient. Finally, its cloaking ability is demonstrated by camouflaging the same heat source in the shape of different objects. Our designed metasurface mitigates the limitations in design and fabrication of existing thermal metamaterials, and can be used in applications requiring large flexibility, thermal illusion, and large thermal gradients on small scales. Materials science ; Thermal conductivity ; Metamaterial ; Fabrication ; Thermal ; Cloak ; Cloaking ; Coating ; Temperature gradient ; Optoelectronics ; Nanotechnology ; Composite material ; Physics Metamaterials and Metasurfaces Applications ; Thermal Radiation and Cooling Technologies ; Acoustic Wave Phenomena Research
Authors: Henri Perrin | Grégory Mertz | Noha-Lys Senoussaoui | Loïc Borghini | Sébastien Klein | Régis Vaudemont
Source: Functional Composite Materials (article, 2021-04-06)
Field: Materials Science — Surfaces, Coatings and Films

Surface functionalization of thermoset composite for infrared hybrid welding Abstract Fusion assembly is a highly promising technique for joining thermoplastic composite to thermoset composites, enabling the use of both the most affordable composite material and process for each substructure. However, some major challenges need to be addressed such as functionalizing the thermoset composite surface through co-curing with an appropriate thermoplastic interlayer or realizing a fast and robust welding process that meets all quality and mechanical requirements. In this paper, we investigated the potential of polyetheretherketone (PEEK) and its amorphous (PEEK A) and semicristalline (PEEK SC) states as interlayer materials, co-cured onto thermoset composites. A surface preparation involving the atmospheric plasma process demonstrated that both PEEK state materials can be used as interlayer with favorable adhesion properties. The influence of the plasma treatment on surface properties and morphology was also experimentally characterized. Thermosetting polymer ; Peek ; Materials science ; Composite material ; Surface modification ; Composite number ; Thermoplastic ; Curing (chemistry) ; Polymer ; Mechanical engineering Surface Modification and Superhydrophobicity ; Fiber-reinforced polymer composites ; Epoxy Resin Curing Processes
Authors: Enikő Bitay | Zoltán‐István Szabó | József Kántor | Kristóf Molnár | Attila Gergely
Source: eXPRESS Polymer Letters (article, 2021-01-01)
Field: Materials Science — Biomaterials

Scale-up and optimization of fenofibrate-loaded fibers electrospun by corona-electrospinning Scaled-up production of fenofibrate-loaded, polyvinylpyrrolidone-based microfibrous mats was achieved by using corona-electrospinning. An experimental design-based approach was used to study the influence of production parameters on fiber diameter and morphology. Microstructural characterization of the obtained products was performed by scanning electron microscopy imaging and differential scanning calorimetry. Drug content and in vitro dissolution studies were performed in order to monitor the effect of electrospinning on the drug release characteristics from the obtained product. The optimized parameters provided electrospun mats with smooth, homogenous fibers, without beading, which conferred rapid drug release and increased solubility of the lipid-lowering drug. The in vitro dissolution results show 40 times higher fenofibrate release from the fiber mats compared to the micronized active pharmaceutical ingredient. The presented results show that corona-electrospinning is a promising method for scale-up applications, and it could be used in the pharmaceutical industry. The fenofibrate loaded microfibrous mats could treat dyslipidemia, thus prevent heart attack or stroke, by using lower drug content. Lower drug content could also reduce the associated side effects and lowers the cost of treatment. Electrospinning ; Materials science ; Polyvinylpyrrolidone ; Fenofibrate ; Dissolution ; Polyvinyl alcohol ; Fiber ; Solubility ; Scanning electron microscope ; Chemical engineering ; Composite material ; Polymer ; Polymer chemistry ; Chemistry ; Pharmacology ; Organic chemistry ; Medicine Electrospun Nanofibers in Biomedical Applications ; Conducting polymers and applications
Authors: TAO HE | SHIBIAO MU | Houkui Zhou | JUNGUO HU
Source: Wood Research (article, 2021-03-02)
Field: Chemistry — Organic Chemistry

Wood species identification based on an ensemble of deep convolution neural networks Our paper proposed an ensemble framework of combining three deep convolution neural networks (CNN). This method was inspired by network in network. Transfer learning used to accelerate training and deeper layers of network. Nine different CNN architectures were trained and evaluated in two wood macroscopic images datasets. After two times of 30 epochs training, our proposed network obtained 100% test rate in our dataset, which including 8 kinds of wood species and 918 images. The proposed method achieved 98.81% test recognition rate after three times training with 30 epochs in other dataset, which including 41 kinds of wood species and 11,984 images. Results showed that magnification macroscopic images can be instead of microscopic images in wood species identification, and our proposed ensemble of deep CNN can be used for wood species identification. Identification (biology) ; Convolution (computer science) ; Artificial neural network ; Artificial intelligence ; Biological system ; Convolutional neural network ; Pattern recognition (psychology) ; Computer science ; Environmental science ; Botany ; Biology Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Image Processing and 3D Reconstruction
Authors: Angelika Wronkowicz | Andrzej Katunin | Marko Nagode | Jernej Klemenc
Source: Sensors (article, 2021-12-14)
Field: Materials Science — Materials Chemistry

Classification of Cracks in Composite Structures Subjected to Low-Velocity Impact Using Distribution-Based Segmentation and Wavelet Analysis of X-ray Tomograms The problem of characterizing the structural residual life is one of the most challenging issues of the damage tolerance concept currently applied in modern aviation. Considering the complexity of the internal architecture of composite structures widely applied for aircraft components nowadays, as well as the additional complexity related to the appearance of barely visible impact damage, prediction of the structural residual life is a demanding task. In this paper, the authors proposed a method based on detection of structural damage after low-velocity impact loading and its classification with respect to types of acting stress on constituents of composite structures using the developed processing algorithm based on segmentation of 3D X-ray computed tomograms using the <b>rebmix</b> package, real-oriented dual-tree wavelet transform and supporting image processing procedures. The presented algorithm allowed for accurate distinguishing of defined types of damage from X-ray computed tomograms with strong robustness to noise and measurement artifacts. The processing was performed on experimental data obtained from X-ray computed tomography of a composite structure with barely visible impact damage, which allowed better understanding of fracture mechanisms in such conditions. The gained knowledge will allow for a more accurate simulation of structural damage in composite structures, which will provide higher accuracy in predicting structural residual life. Robustness (evolution) ; Residual ; Segmentation ; Computer science ; Wavelet transform ; Residual stress ; Algorithm ; Tomography ; Wavelet ; Composite number ; Structural engineering ; Artificial intelligence ; Engineering ; Materials science ; Optics ; Composite material Material Properties and Failure Mechanisms ; Industrial Engineering and Technologies ; Mining and Gasification Technologies
Authors: Gareth W. Richings | Scott Habershon
Source: Molecules (article, 2021-12-07)
Field: Chemistry — Spectroscopy

Analyzing Grid-Based Direct Quantum Molecular Dynamics Using Non-Linear Dimensionality Reduction Grid-based schemes for simulating quantum dynamics, such as the multi-configuration time-dependent Hartree (MCTDH) method, provide highly accurate predictions of the coupled nuclear and electronic dynamics in molecular systems. Such approaches provide a multi-dimensional, time-dependent view of the system wavefunction represented on a coordinate grid; in the case of non-adiabatic simulations, additional information about the state populations adds a further layer of complexity. As such, wavepacket motion on potential energy surfaces which couple many nuclear and electronic degrees-of-freedom can be extremely challenging to analyse in order to extract physical insight beyond the usual expectation-value picture. Here, we show that non-linear dimensionality reduction (NLDR) methods, notably diffusion maps, can be adapted to extract information from grid-based wavefunction dynamics simulations, providing insight into key nuclear motions which explain the observed dynamics. This approach is demonstrated for 2-D and 9-D models of proton transfer in salicylaldimine, as well as 8-D and full 12-D simulations of <i>cis</i>-<i>trans</i> isomerization in ethene; these simulations demonstrate how NLDR can provide alternative views of wavefunction dynamics, and also highlight future developments. Wave function ; Hartree ; Degrees of freedom (physics and chemistry) ; Statistical physics ; Dimensionality reduction ; Quantum dynamics ; Wave packet ; Molecular dynamics ; Quantum ; Curse of dimensionality ; Physics ; Computer science ; Quantum mechanics ; Artificial intelligence Advanced NMR Techniques and Applications ; NMR spectroscopy and applications ; Quantum, superfluid, helium dynamics
Authors: Matthew K. Horton | Rachel Woods-Robinson
Source: Patterns (article, 2021-12-01)
Field: Materials Science — Materials Chemistry

Addressing the critical need for open experimental databases in materials science With the HTEM, an open online database containing experimental synthesis and characterization data of thin film inorganic materials, Talley et al. (2021) lay a foundation for a new era of high-throughput materials design. Foundation (evidence) ; Characterization (materials science) ; Key (lock) ; Open source Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Catalysis and Oxidation Reactions
Authors: Luca Mazzei | Francesco Musiani | Szymon Żerko | Wiktor Koźmiński | Michele Cianci | Ylenia Beniamino | Stefano Ciurli | Barbara Zambelli
Source: Metallomics (article, 2021-11-25)
Field: Chemistry — Inorganic Chemistry

Structure, dynamics, and function of SrnR, a transcription factor for nickel-dependent gene expression Streptomyces griseus, a bacterium producing antibacterial drugs and featuring possible application in phytoremediation, expresses two metal-dependent superoxide dismutase (SOD) enzymes, containing either Fe(II) or Ni(II) in their active site. In particular, the alternative expression of the two proteins occurs in a metal-dependent mode, with the Fe(II)-enzyme gene (sodF) repressed at high intracellular Ni(II) concentrations by a two-component system (TCS). This complex involves two proteins, namely SgSrnR and SgSrnQ, which represent the transcriptional regulator and the Ni(II) sensor of the system, respectively. SgSrnR belongs to the ArsR/SmtB family of metal-dependent transcription factors; in the apo-form and in the absence of SgSrnQ, it can bind the DNA operator of sodF, upregulating gene transcription. According to a recently proposed hypothesis, Ni(II) binding to SgSrnQ would promote its interaction with SgSrnR, causing the release of the complex from DNA and the consequent downregulation of the sodF expression. SgSrnQ is predicted to be highly disordered, thus the understanding, at the molecular level, of how the SgSrnR/SgSrnQ TCS specifically responds to Ni(II) requires the knowledge of the structural, dynamic, and functional features of SgSrnR. These were investigated synergistically in this work using X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, atomistic molecular dynamics calculations, isothermal titration calorimetry, and in silico molecular docking. The results reveal that the homodimeric apo-SgSrnR binds to its operator in a two-step process that involves the more rigid globular portion of the protein and leaves its largely disordered regions available to possibly interact with the disordered SgSrnQ in a Ni-dependent process. Isothermal titration calorimetry ; Transcription factor ; Transcription (linguistics) ; Chemistry ; Gene expression ; Gene ; Biochemistry ; Biophysics ; Biology Metal-Catalyzed Oxygenation Mechanisms ; Environmental remediation with nanomaterials ; Radioactive element chemistry and processing
Authors: Ch. Ravi Teja | K. Abraham Peele | Neeraja Vallur | K. Mamatha | John Babu Dulla | T. C. Venkateswarulu | Vidya Prabhakar Kodali
Source: Journal of Genetic Engineering and Biotechnology (article, 2021-03-12)
Field: Materials Science — Biomaterials

Antioxidant potential and optimization of production of extracellular polysaccharide by Acinetobacter indicus M6 Acinetobacter indicus M6 bacterium produces a novel and unique extracellular heteropolysaccharide with highly efficient antioxidant activity. GC-MS analyses elucidated the presence of quite uncommon (1→4)-linked glucose, (1→4)-linked mannose, and (→4)-GlcN-(1→) glycosidic linkages in the backbone. The optimized medium improved the production of ECP and is two folds higher in comparison with the basal medium. The newly optimized medium could be used as a promising alternative for the overproduction of ECP. DPPH ; Polysaccharide ; Chemistry ; Yeast extract ; Mannose ; Food science ; Antioxidant ; Extracellular polysaccharide ; Acinetobacter ; Biochemistry ; Response surface methodology ; Bacteria ; Chromatography ; Biology ; Fermentation ; Antibiotics biodegradable polymer synthesis and properties ; Bacterial biofilms and quorum sensing ; Enzyme Catalysis and Immobilization
Authors: Jack B. Greisman | Kevin M. Dalton | Doeke R. Hekstra
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-02-04)
Field: Materials Science — Materials Chemistry

Reciprocalspaceship: A Python Library for Crystallographic Data Analysis A bstract X-ray crystallography is an invaluable technique for studying the atomic structure of macromolecules. Much of crystallography’s success is due to the software packages developed to enable the automated processing of diffraction data. However, the analysis of unconventional diffraction experiments can still pose significant challenges—many existing programs are closed-source, sparsely documented, or are challenging to integrate with modern libraries for scientific computing and machine learning. Here we describe reciprocalspaceship , a Python library for exploring reciprocal space. It provides a tabular representation for reflection data from diffraction experiments that extends the widely-used pandas library with built-in methods for handling space group, unit cell, and symmetry-based operations. As we illustrate, this library facilitates new modes of exploratory data analysis while supporting the prototyping, development, and release of new methods. Python (programming language) ; Computer science ; Software ; Reciprocal lattice ; Crystallography ; Diffraction ; Chemistry ; Programming language ; Physics ; Optics Enzyme Structure and Function ; Machine Learning in Materials Science ; Protein Structure and Dynamics
Authors: Xiaolong Shi | Zhi Zhang | Lanjie Wu | Xincai Li | Zhenwu Zhang
Source: Coatings (article, 2021-10-20)
Field: Materials Science — Materials Chemistry

Corrosion Law of Metal Pipeline in Tahe Oilfield and Application of New Materials Frequent corrosion perforation of metal pipes severely restricts oil and gas fields’ safety production and increases maintenance costs. Therefore, it is imminent to change the characteristics of metal materials fundamentally. In this paper, taking the metal pipe of Northwest Oil and Gas Field in China as an example, for the corrosion environment with high concentrations of H2S, CO2, H2O, Cl−, and O2, the main factors leading to corrosion are analyzed, the corrosion rules and optical materials of the pipe under different environmental and operating conditions are figured out, and the corrosion resistance of new pipes materials is evaluated. The main conclusions are as follows: (1) In the environment of the CO2–H2O–Cl− strong scouring system, electrochemical corrosion dominates, and the corrosion morphology is mainly groove-like corrosion and ulcer-like corrosion; (2) The H2S content affects the incubation period and development period of pipe corrosion; (3) Through the two optimization directions of 20# steel refining and material alloying, BX245-1Cr pipe material has been developed. At present, the application of this pipe material has relatively better results. Corrosion ; Perforation ; Materials science ; Metallurgy ; Pipeline transport ; Metal ; Groove (engineering) ; Environmental science ; Environmental engineering Corrosion Behavior and Inhibition ; Structural Integrity and Reliability Analysis ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Wojciech Koch | Wirginia Kukuła‐Koch | Marcin Czop | Tomasz Baj | Janusz Kocki | Piotr Bawiec | Olivier Casasnovas | Anna Głowniak-Lipa | Kazimierz Głowniak
Source: Molecules (article, 2021-10-04)
Field: Chemistry — Analytical Chemistry

Analytical Assessment of Bioelements in Various Types of Black Teas from Different Geographical Origins in View of Chemometric Approach A comprehensive approach to the mineral composition of black teas of different origins was studied using the Flame Atomic Absorption Spectrometry (FAAS) method, supported by chemometric tools including Principal Component Analysis PCA) and Classification and Regression Trees (CART). Significant differences between the teas from seven countries (Japan, Nepal, Kenya, Iran, Sri Lanka, India, and China) were shown. K was the main element determined in all teas, with an average concentration of 11,649 mg/kg, followed by Ca, Mg and Mn. In general, regarding all investigated black teas, the element content was ranked in the following order: K > Ca > Mg > Mn > Fe > Na > Zn > Cu. The applied chemometric methods allowed us to recognize black tea clusters based on their mineral composition and place of cultivation, and allowed us to find correlations between particular elements in black teas. The performed analyses revealed interesting correlations between the concentration of various elements in black teas: K was negatively correlated with Na, Fe, Mn and Cu; K was positively correlated with the content of Ca and Mg. Significant positive correlations between Mn and Fe and Mn and Zn in the studied black tea samples were also revealed. It was shown that mineral composition may be a significant factor regarding the origin of the black tea, not only considering the country, but also the region or province. Black tea ; Chemistry ; Principal component analysis ; Mineral ; Composition (language) ; Atomic absorption spectroscopy ; Analytical Chemistry (journal) ; Mineralogy ; Environmental chemistry ; Food science ; Mathematics ; Statistics ; Physics Heavy Metals in Plants ; Tea Polyphenols and Effects ; Phytochemicals and Antioxidant Activities