jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Wenjie Qi | Zehao Huang | Zheming Chen | Lijuan Fu | Zhigang Zhang
Source: RSC Advances (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Experimental and theoretical investigation of oxidative methane activation on Pd–Pt catalysts Density functional theory (DFT) and measurements of rate are used to provide evidence for the rate determining step (RDS) and requirements of the active site for CH<sub>4</sub> combustion on Pd-Pt bimetallic catalysts in five different distinct kinetic regimes. These five regimes exhibit different rate equations for methane combustion due to the reaction rate constants and diverse dominant adsorbed species for these different kinetically relevant steps. Oxygen chemical potential at the Pd-Pt surface was replaced by oxygen pressure, reflecting the kinetic coupling between C-H and O[double bond, length as m-dash]O bond cleavage steps. C-H bond cleavage occurs on different active sites in five of these kinetic regimes, evolving from vacancy-vacancy (*-*) to oxygen-vacancy (O*-*), oxygen-oxygen (O*-O*) site pairs, monolayer Pd-O, and ultimately to oxide bulk with Pd-O site pairs as the oxygen chemical potential increases. It is easier to form a metallic surface at low oxygen pressure, implying minimal O* coverage. The sole kinetically relevant step on uncovered Pd-Pt surfaces for methane combustion is O[double bond, length as m-dash]O bond cleavage. The supply of oxygen is obviously more important than the supply of methane in regime (I). As vacancies become less available on metallic surfaces, C-H bond cleavage occurs <i>via</i> O*-* paired sites, the energy barrier of which is much higher than that on uncovered Pd-Pt surfaces. In this regime (II), O[double bond, length as m-dash]O bond cleavage is still an irreversible process because O* will be consumed by the rapidly formed products of methane dissociation. For the oxygen saturated surfaces in regime (III), C-H bond cleavage occurs on two adjacent adsorbed oxygens that form OH and weak CH<sub>3</sub>-O bond interactions, resulting in a low activity for methane combustion. On the oxidation surfaces (IV and V), exposed metal atoms and their adjacent exposed lattice oxygen were the active sites, leading to a large decrease in C-H bond cleavage energy barrier, deduced from both experiment and theory. The increase of the metallic oxide thickness (increase of oxygen potential) increases the methane combustion turnover rates on Pd-Pt catalysts. Catalysis ; Oxygen ; Chemistry ; Bond cleavage ; Methane ; Oxide ; Density functional theory ; Bimetallic strip ; Monolayer ; Kinetic energy ; Photochemistry ; Computational chemistry ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Catalysts for Methane Reforming
Authors: Chaochao Yan | Sheng Wang | Jinyu Yang | Tingyang Xu | Junzhou Huang
Source: arXiv (Cornell University) (preprint, 2019-10-01)
Field: Materials Science — Materials Chemistry

Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation Molecule generation is to design new molecules with specific chemical properties and further to optimize the desired chemical properties. Following previous work, we encode molecules into continuous vectors in the latent space and then decode the vectors into molecules under the variational autoencoder (VAE) framework. We investigate the posterior collapse problem of current RNN-based VAEs for molecule sequence generation. For the first time, we find that underestimated reconstruction loss leads to posterior collapse, and provide both theoretical and experimental evidence. We propose an effective and efficient solution to fix the problem and avoid posterior collapse. Without bells and whistles, our method achieves SOTA reconstruction accuracy and competitive validity on the ZINC 250K dataset. When generating 10,000 unique valid SMILES from random prior sampling, it costs JT-VAE1450s while our method only needs 9s. Our implementation is at https://github.com/chaoyan1037/Re-balanced-VAE. Autoencoder ; Sequence (biology) ; Computer science ; ENCODE ; Sampling (signal processing) ; Algorithm ; Encoding (memory) ; Artificial intelligence ; Chemistry ; Computer vision ; Artificial neural network Machine Learning in Materials Science ; Molecular Biology Techniques and Applications ; Mass Spectrometry Techniques and Applications
Authors: Jeefferie Abd Razak | Noraiham Mohamad | Mazlin Aida Mahamood | Rosidah Jaafar | Intan Sharhida Othman | Mohd Muzafar Ismail | Kok-Tee Lau | Ramli Junid | Zaleha Mustafa
Source: JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES (article, 2019-09-27)
Field: Materials Science — Polymers and Plastics

On the preparation of EPDM-g-MAH compatibilizer via melt-blending method This paper presents an experimental investigation to determine the optimum composition of maleic anhydride (MAH) and dicumyl peroxide (DCP) as initiator for ethylene-propylene-diene-monomer grafted MAH (EPDM-g-MAH) compatibilizer preparation, using response surface methodology (RSM) approach. EPDM-g-MAH was prepared in the laboratory scale by melt blending method using an internal mixer. For this study, the effects of MAH (2.50 – 7.50 wt.%) and DCP (0.10 – 0.30 wt.%) towards grafting efficiency was determined. Two level full factorial design of experiment (DOE) is applied to establish the relationship between these two independent factors of raw materials. Analysis of variance (ANOVA) and the optimization menu were utilized to decide the raw materials formulation with maximum grafting efficiency. Quantitative analysis based on infra-red (IR) spectral intensity supported by 1H-NMR spectral are used to propose for EPDM-g-MAH grafting mechanism. Standard calibration curve for quantity ratio plot was exponential with R2 = 89.19%. It was found that an optimum about 8.52% of MAF grafting efficiency has been yielded with DCP factor has contributed larger effect at 67.45% of contribution effect. Anhydride stretching of grafted C=O as confirmed by FTIR peak at 1713 cm-1 and 1770 – 1792 cm-1 has responsible for MAH grafting into EPDM rubber. Based on FTIR, 1H-NMR and 2D-COSY spectral analysis, reaction mechanism for EPDM-g-MAH grafting was successfully proposed with two possible termination steps. Maleic anhydride ; Materials science ; Grafting ; Fourier transform infrared spectroscopy ; Monomer ; Factorial experiment ; Natural rubber ; Raw material ; Yield (engineering) ; Compatibilization ; Ethylene propylene rubber ; Chemical engineering ; Composite material ; Polymer chemistry ; Polymer ; Copolymer ; Polymer blend ; Mathematics ; Organic chemistry ; Chemistry Polymer Nanocomposites and Properties ; Asphalt Pavement Performance Evaluation ; Tribology and Wear Analysis
Authors: Luis Prent-Peñaloza | Alexander F. de la Torre | José Luís Velázquez‐Libera | Margarita Gutiérrez | Julio Caballero
Source: Molecules (article, 2019-01-06)
Field: Chemistry — Organic Chemistry

Synthesis of diN-Substituted Glycyl-Phenylalanine Derivatives by Using Ugi Four Component Reaction and Their Potential as Acetylcholinesterase Inhibitors Ugi four component reaction (Ugi-4CR) isocyanide-based multicomponent reactions were used to synthesize diN-substituted glycyl-phenylalanine (diNsGF) derivatives. All of the synthesized compounds were characterized by spectroscopic and spectrometric techniques. In order to evaluate potential biological applications, the synthesized compounds were tested in computational models that predict the bioactivity of organic molecules by using only bi-dimensional molecular information. The diNsGF derivatives were predicted as cholinesterase inhibitors. Experimentally, all of the synthesized diNsGF derivatives showed moderate inhibitory activities against acetylcholinesterase (AChE) and poor activities against butyrylcholinesterase (BuChE). Compound <b>7a</b> has significant activity and selectivity against AChE, which reveals that the diNsGF scaffold could be improved to reach novel candidates by combining other chemical components of the Ugi-4CR in a high-throughput combinatorial screening experiment. Molecular docking experiments of diNsGF derivatives inside AChE suggest that these compounds placed the phenylalanine group at the peripheral site of AChE. The orientations and chemical interactions of diNsGF derivatives were analyzed, and the changeable groups were identified for future exploration of novel candidates that could lead to the improvement of diNsGF derivative inhibitory activities. Acetylcholinesterase ; Butyrylcholinesterase ; Ugi reaction ; Chemistry ; Phenylalanine ; Combinatorial chemistry ; Isocyanide ; Cholinesterase ; Selectivity ; Docking (animal) ; Aché ; Enzyme ; Stereochemistry ; Organic chemistry ; Amino acid ; Biochemistry ; Catalysis ; Pharmacology Multicomponent Synthesis of Heterocycles ; Computational Drug Discovery Methods ; Synthesis and biological activity
Authors: Peter Woerner | Aditya Nair | Kunihiko Taira | William S. Oates
Source: PLoS ONE (article, 2019-04-12)
Field: Materials Science — Materials Chemistry

Sparsification of long range force networks for molecular dynamics simulations Atomic interactions in solid materials are described using network theory. The tools of network theory focus on understanding the properties of a system based upon the underlying interactions which govern their dynamics. While the full atomistic network is dense, we apply a spectral sparsification technique to construct a sparse interaction network model that reduces the computational complexity while preserving macroscopic conservation properties. This sparse network is compared to a reduced network created using a cut-off radius (threshold method) that is commonly used to speed-up computations while approximating interatomic forces. The approximations used to estimate the total forces on each atom are quantified to assess how local interatomic force errors propagate errors at the global or continuum scale by comparing spectral sparsification to thresholding. In particular, we quantify the performance of the spectral sparsification algorithm for the short-range Lennard-Jones potential and the long-range Coulomb potential. Spectral sparsification of the Lennard-Jones potential yields comparable results to thresholding while spectral sparsification yields improvements when considering a long-range Coulomb potential. The present network-theoretic formulation is implemented on two sample problems: relaxation of atoms near a surface and a tensile test of a solid with a circular hole. Statistical physics ; Molecular dynamics ; Computation ; Range (aeronautics) ; Physics ; Thresholding ; Interatomic potential ; Coulomb ; Algorithm ; Computer science ; Materials science ; Quantum mechanics ; Artificial intelligence Thermal properties of materials ; Machine Learning in Materials Science ; Nanopore and Nanochannel Transport Studies
Authors: Amal Aboulhassan | Markus Hadwiger | Olga Wodo
Source: Computational Materials Science (article, 2019-12-02)
Field: Materials Science — Materials Chemistry

Extracting topology, shape and size from heterogenous microstructure Microstructure ; Topology (electrical circuits) ; Representation (politics) ; Materials science ; Process (computing) ; Computer science ; Topology optimization ; Salient ; Nanotechnology ; Artificial intelligence ; Composite material ; Engineering ; Finite element method Machine Learning in Materials Science ; Nanoporous metals and alloys ; Advanced Memory and Neural Computing
Authors: F. Aaron Cruz-Navarrete | Nicola J. Baxter | Henry P. Wood | Andrea M. Hounslow | Jonathan P. Waltho
Source: Biomolecular NMR Assignments (article, 2019-08-08)
Field: Materials Science — Materials Chemistry

1H, 15N and 13C backbone resonance assignments of the P146A variant of β-phosphoglucomutase from Lactococcus lactis in its substrate-free form β-Phosphoglucomutase (βPGM) is a magnesium-dependent phosphoryl transfer enzyme that catalyses the reversible isomerisation of β-glucose 1-phosphate and glucose 6-phosphate, via two phosphoryl transfer steps and a β-glucose 1,6-bisphosphate intermediate. Substrate-free βPGM is an essential component of the catalytic cycle and an understanding of its dynamics would present significant insights into βPGM functionality, and enzyme catalysed phosphoryl transfer in general. Previously, 30 residues around the active site of substrate-free βPGM<sub>WT</sub> were identified as undergoing extensive millisecond dynamics and were unassignable. Here we report <sup>1</sup>H, <sup>15</sup>N and <sup>13</sup>C backbone resonance assignments of the P146A variant (βPGM<sub>P146A</sub>) in its substrate-free form, where the K145-A146 peptide bond adopts a trans conformation in contrast to all crystal structures of βPGM<sub>WT</sub>, where the K145-P146 peptide bond is cis. In βPGM<sub>P146A</sub> millisecond dynamics are suppressed for all but 17 residues, allowing 92% of backbone resonances to be assigned. Secondary structure predictions using TALOS-N reflect βPGM crystal structures, and a chemical shift comparison between substrate-free βPGM<sub>P146A</sub> and βPGM<sub>WT</sub> confirms that the solution conformations are very similar, except for the D137-A147 loop. Hence, the isomerisation state of the 145-146 peptide bond has little effect on structure but the cis conformation triggers millisecond dynamics in the hinge (V12-T16), the nucleophile (D8) and residues that coordinate the transferring phosphate group (D8 and S114-S116), and the D137-A147 loop (V141-A142 and K145). These millisecond dynamics occur in addition to those for residues involved in coordinating the catalytic Mg<sup>II</sup> ion and the L44-L53 loop responsible for substrate discrimination. Lactococcus lactis ; Phosphoglucomutase ; Substrate (aquarium) ; Resonance (particle physics) ; Chemistry ; Biochemistry ; Computational biology ; Biology ; Genetics ; Bacteria ; Physics ; Enzyme ; Particle physics ; Ecology ; Lactic acid Enzyme Structure and Function ; Amino Acid Enzymes and Metabolism ; Metabolism and Genetic Disorders
Authors: Sanja Sviben | Oliver Spaeker | Mathieu Bennet | Marie Albéric | Jan‐Henning Dirks | Bernard Moussian | Peter Fratzl | Luca Bertinetti | Yael Politi
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-10-05)
Field: Materials Science — Biomaterials

Epidermal cell surface structure and chitin-protein co-assembly determine fiber architecture in the Locust cuticle Summary The geometrical similarity of helicoidal fiber arrangement in many biological fibrous extracellular matrices, such as bone, plant cell wall or arthropod cuticle, to that of cholesteric liquid mesophases has led to the hypothesis that they may form passively through a mesophase precursor rather than by direct cellular control. In search of direct evidence to support or refute this hypothesis, here, we studied the process of cuticle formation in the tibia of the migratory locust, Locusta migratoria , where daily growth layers arise by the deposition of fiber arrangements alternating between unidirectional and helicoidal structures. Using FIB/SEM volume imaging and scanning X-ray scattering, we show that the epidermal cells determine an initial fiber orientation from which the final architecture emerges by the self-organized co-assembly of chitin and proteins. Fiber orientation in the locust cuticle is therefore determined by both active and passive processes. Cuticle (hair) ; Chitin ; Arthropod cuticle ; Fiber ; Locust ; Nanofiber ; Biophysics ; Mesophase ; Materials science ; Cell wall ; Biology ; Nanotechnology ; Anatomy ; Composite material ; Botany ; Liquid crystal ; Insect ; Biochemistry ; Optoelectronics Calcium Carbonate Crystallization and Inhibition ; Insect and Arachnid Ecology and Behavior ; Magnetic and Electromagnetic Effects
Authors: Jonáš Hruška | Telmo Adão | Luís Pádua | Nathalie Guimarães | Emanuel Peres | Raul Morais | Joaquim J. Sousa
Source: The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences (article, 2019-08-21)
Field: Chemistry — Analytical Chemistry

EVALUATION OF MACHINE LEARNING TECHNIQUES IN VINE LEAVES DISEASE DETECTION: A PRELIMINARY CASE STUDY ON FLAVESCENCE DORÉE Abstract. Vine culture is influenced by many factors, such as the weather, soil or topography, which are triggers to phytosanitary issues. Among them are some diseases, that are responsible for major economic losses that can, however, be managed with timely interventions in the field, viable of leading to effective results by preventing damage propagation. While not all symptoms might present a visible evidence, hyperspectral sensors can tackle this aspect with their ability for measuring hundreds of continuously sparse bands that range beyond the eye-perceptible spectrum. Having such research line in mind in this work, a hyperspectral sensor was applied to analyse the spectral status of vine leaves samples, collected in three chronologically distinct campaigns, while costly and destructive laboratory methods were used to track Flavescence Dorée (FD) in the same samples, for a ground truth information. Regarding data processing, machine learning approaches were used, in which several classifiers were selected to detect FD in vine leaves hyperspectral images. The goal was to evaluate and find most suitable classifier for this task. Hyperspectral imaging ; Vine ; Computer science ; Phytosanitary certification ; Artificial intelligence ; Machine learning ; Classifier (UML) ; Agricultural engineering ; Pattern recognition (psychology) ; Biology ; Horticulture ; Engineering Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Horticultural and Viticultural Research
Authors: Ahmedhan Emilevich Shabanov | Mikhail Nikolaevich Petrov | Alexander Viktorovich Chikitkin
Source: Computer Research and Modeling (article, 2019-04-01)
Field: Chemistry — Analytical Chemistry

A multilayer neural network for determination of particle size distribution in Dynamic Light Scattering problem . , , . , . , , . , , 1-500 . 60 RELU , 45 , dropout 2 15 1 ( ). , . (rmse) 1.3157 . 200 , 400 . , . : , , . , Dynamic light scattering ; Dropout (neural networks) ; Artificial neural network ; Particle-size distribution ; Light scattering ; Particle (ecology) ; Scattering ; Biological system ; Particle size ; Computer science ; Statistical physics ; Distribution (mathematics) ; Physics ; Artificial intelligence ; Optics ; Mathematics ; Machine learning ; Chemistry ; Nanotechnology ; Materials science ; Mathematical analysis ; Biology ; Physical chemistry Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Effects of Environmental Stressors on Livestock
Authors: Marius Olteanu | Nicolae Paraschiv | Petia Koprinkova‐Hristova
Source: Cybernetics and Information Technologies (article, 2019-06-01)
Field: Materials Science — Biomaterials

Genetic Algorithms vs. Knowledge-Based Control of PHB Production Abstract The paper proposes an approach using Genetic Algorithm (GA) for development of optimal time profiles of key control variable of Poly-HydroxyButyrate (PHB) production process. Previous work on modeling and simulation of PHB process showed that it is a highly nonlinear process that needs special controllers based on human experience, as such fuzzy logic controller proved to be a good choice. Fuzzy controllers are not totally replaced, due to the specific process knowledge that they contain. The achieved results are compared with previously proposed knowledge-based approach to the same optimal control task. Computer science ; Task (project management) ; Fuzzy logic ; Key (lock) ; Controller (irrigation) ; Process (computing) ; Production (economics) ; Genetic algorithm ; Control (management) ; Process control ; Fuzzy control system ; Algorithm ; Nonlinear system ; Control engineering ; Artificial intelligence ; Machine learning ; Engineering ; Systems engineering biodegradable polymer synthesis and properties ; Advanced Control Systems Optimization ; Fuzzy Logic and Control Systems
Authors: Tulio A. Lerma | Mindtech s.a.s | Jina M. Martínez | Enrique M Combatt
Source: Journal of Science with Technological Applications (article, 2019-05-01)
Field: Chemistry — Analytical Chemistry

Determination of total protein content by digital image analysis: an approach for food quality remote analysis The objective of this work was to evaluate the potential of digital image analysis based on color (DIAC), using surface color index defined for RGB space, for the determination of total protein content (TPC) by Biuret method. Approximation of surface color index was used to describe quantitatively the color intensity in the digital image of samples and standards. It was concluded that DIAC is a fast and simple analytical alternative for the determination of TPC. Detection and quantification limits were 0.02 mg/mL and 0.08 mg/mL, respectively. In addition, measurements of absorbance can be satisfactorily correlated with measurements of surface color intensity (R 2 = 0.9957). In addition, the importance of control of internal brightness in the measuring device was evidenced from distribution of values of color intensity into the images. It was concluded that DIAC is a Content analysis ; Computer science ; Quality (philosophy) ; Food science ; Digital image analysis ; Computer vision ; Chemistry ; Sociology ; Physics Spectroscopy and Chemometric Analyses
Authors: Anastasiya Toenjes | Heike Sonnenberg | Christina Plump | Rolf Drechsler | Axel von Hehl
Source: Metals (article, 2019-01-29)
Field: Chemistry — Physical and Theoretical Chemistry

Measurement and Evaluation of Calorimetric Descriptors for the Suitability for Evolutionary High-Throughput Material Development A novel method for evolutionary material development by using high-throughput processing is established. For the purpose of this high-throughput approach, spherical micro samples are used, which have to be characterized, up-scaled to macro level and valued. For the evaluation of the microstructural state of the micro samples and the associated micro-properties, fast characterization methods based on physical testing methods such as calorimetry and universal microhardness measurements are developed. Those measurements result in so-called descriptors. The increase in throughput during calorimetric characterization using differential scanning calorimetry is achieved by accelerating the heating rate. Consequently, descriptors are basically measured in a non-equilibrium state. The maximum heating rate is limited by the possibility to infer the microstructural state from the calorimetric results. The substantial quality of the measured descriptors for micro samples has to be quantified and analyzed depending on the heating rate. In this work, the first results of the measurements of calorimetric descriptors with increased heating rates for 100Cr6 will be presented and discussed. The results of low and high heating rates will be compared and analyzed using additional microhardness measurements. Furthermore, the validation of the method regarding the suitability for the evolutionary material development includes up-scaling to macro level and therefore different sample masses will be investigated using micro and macro samples during calorimetry. Differential scanning calorimetry ; Calorimetry ; Throughput ; Materials science ; Biological system ; Macro ; Characterization (materials science) ; Scaling ; Indentation hardness ; Thermodynamics ; Nanotechnology ; Computer science ; Mathematics ; Microstructure ; Composite material ; Physics ; Biology thermodynamics and calorimetric analyses ; Machine Learning in Materials Science ; Calcium Carbonate Crystallization and Inhibition