jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Wells Utembe | Victor Wepener | Il Je Yu | Mary Gulumian
Source: Environmental Toxicology and Chemistry (review, 2018-08-17)
Field: Materials Science — Materials Chemistry

An assessment of applicability of existing approaches to predicting the bioaccumulation of conventional substances in nanomaterials The experimental determination of bioaccumulation is challenging, and a number of approaches have been developed for its prediction. It is important to assess the applicability of these predictive approaches to nanomaterials (NMs), which have been shown to bioaccumulate. The octanol/water partition coefficient (K<sub>OW</sub> ) may not be applicable to some NMs that are not found in either the octanol or water phases but rather are found at the interface. Thus the K<sub>OW</sub> values obtained for certain NMs are shown not to correlate well with the experimentally determined bioaccumulation. Implementation of quantitative structure-activity relationships (QSARs) for NMs is also challenging because the bioaccumulation of NMs depends on nano-specific properties such as shape, size, and surface area. Thus there is a need to develop new QSAR models based on these new nanodescriptors; current efforts appear to focus on digital processing of NM images as well as the conversion of surface chemistry parameters into adsorption indices. Water solubility can be used as a screening tool for the exclusion of NMs with short half-lives. Adaptation of fugacity/aquivalence models, which include physicochemical properties, may give some insights into the bioaccumulation potential of NMs, especially with the addition of a biota component. The use of kinetic models, including physiologically based pharmacokinetic models, appears to be the most suitable approach for predicting bioaccumulation of NMs. Furthermore, because bioaccumulation of NMs depends on a number of biotic and abiotic factors, it is important to take these factors into account when one is modeling bioaccumulation and interpreting bioaccumulation results. Environ Toxicol Chem 2018;37:2972-2988. © 2018 SETAC. Bioaccumulation ; Environmental chemistry ; Environmental science ; Biochemical engineering ; Chemistry ; Engineering Nanoparticles: synthesis and applications ; Analytical chemistry methods development ; Electrochemical Analysis and Applications
Authors: Flávio Marcelo Correia | José Vicente Hallak Dangelo | Gustavo Almeida | Sueli Aparecida Mingoti
Source: Brazilian Journal of Chemical Engineering (article, 2018-09-01)
Field: Chemistry — Analytical Chemistry

PREDICTING KAPPA NUMBER IN A KRAFT PULP CONTINUOUS DIGESTER: A COMPARISON OF FORECASTING METHODS This paper discusses kappa number prediction models using Single Exponential Smoothing, Multiple Linear Regression Analysis, the Time Series Method of Box-Jenkins (ARIMA) and Artificial Neural Networks. Applying a database of an industrial eucalyptus Kraft pulp continuous digester, these four different methods were evaluated according to different statistical decision criteria. After fitting the parameters of the models, validations were performed using a new dataset. Results, advantages and limitations of the four methods were compared. Some statistical forecasting indexes indicate that the ARIMA model showed more accurate estimation results, achieving a MAPE lower than 3 % and over 90% of the prediction data deviations lower than one kappa unit. Kappa number ; Autoregressive integrated moving average ; Exponential smoothing ; Artificial neural network ; Mathematics ; Kraft process ; Linear regression ; Statistics ; Kraft paper ; Engineering ; Time series ; Computer science ; Artificial intelligence ; Pulp and paper industry Spectroscopy and Chemometric Analyses ; Mineral Processing and Grinding ; Material Properties and Processing
Authors: Yifei Pei | Qingzhi Zhang | Zhi‐Tian Zuo | Yuanzhong Wang
Source: Molecules (article, 2018-12-17)
Field: Chemistry — Analytical Chemistry

Comparison and Identification for Rhizomes and Leaves of Paris yunnanensis Based on Fourier Transform Mid-Infrared Spectroscopy Combined with Chemometrics <i>Paris polyphylla</i>, as a traditional herb with long history, has been widely used to treat diseases in multiple nationalities of China. Nevertheless, the quality of <i>P. yunnanensis</i> fluctuates among from different geographical origins, so that a fast and accurate classification method was necessary for establishment. In our study, the geographical origin identification of 462 <i>P. yunnanensis</i> rhizome and leaf samples from Kunming, Yuxi, Chuxiong, Dali, Lijiang, and Honghe were analyzed by Fourier transform mid infrared (FT-MIR) spectra, combined with partial least squares discriminant analysis (PLS-DA), random forest (RF), and hierarchical cluster analysis (HCA) methods. The obvious cluster tendency of rhizomes and leaves FT-MIR spectra was displayed by principal component analysis (PCA). The distribution of the variable importance for the projection (VIP) was more uniform than the important variables obtained by RF, while PLS-DA models obtained higher classification abilities. Hence, a PLS-DA model was more suitably used to classify the different geographical origins of <i>P. yunnanensis</i> than the RF model. Additionally, the clustering results of different geographical origins obtained by HCA dendrograms also proved the chemical information difference between rhizomes and leaves. The identification performances of PLS-DA and the RF models of leaves FT-MIR matrixes were better than those of rhizomes datasets. In addition, the model classification abilities of combination datasets were higher than the individual matrixes of rhizomes and leaves spectra. Our study provides a reference to the rational utilization of resources, as well as a fast and accurate identification research for <i>P. yunnanensis</i> samples. Rhizome ; Principal component analysis ; Hierarchical clustering ; Chemometrics ; Pattern recognition (psychology) ; Linear discriminant analysis ; Partial least squares regression ; Mathematics ; Dendrogram ; Artificial intelligence ; Botany ; Statistics ; Cluster analysis ; Traditional medicine ; Computer science ; Biology ; Machine learning ; Population ; Medicine Spectroscopy and Chemometric Analyses ; Traditional Chinese Medicine Analysis ; Phytochemistry and Biological Activities
Authors: Xiangyun Ma | Xueqing Sun | Huijie Wang | Yang Wang | Da Chen | Qifeng Li
Source: Frontiers in Chemistry (article, 2018-09-10)
Field: Chemistry — Analytical Chemistry

Raman Spectroscopy for Pharmaceutical Quantitative Analysis by Low-Rank Estimation Raman spectroscopy has been widely used for quantitative analysis in biomedical and pharmaceutical applications. However, the signal-to-noise ratio (SNR) of Raman spectra is always poor due to weak Raman scattering. The noise in Raman spectral dataset will limit the accuracy of quantitative analysis. Because of high correlations in the spectral signatures, Raman spectra have the low-rank property, which can be used as a constraint to improve Raman spectral SNR. In this paper, a simple and feasible Raman spectroscopic analysis method by Low-Rank Estimation (LRE) is proposed. The Frank-Wolfe (FW) algorithm is applied in the LRE method to seek the optimal solution. The proposed method is used for the quantitative analysis of pharmaceutical mixtures. The accuracy and robustness of Partial Least Squares (PLS) and Support Vector Machine (SVM) chemometric models can be improved by the LRE method. Raman spectroscopy ; Robustness (evolution) ; Rank (graph theory) ; Chemometrics ; Biological system ; Partial least squares regression ; Analytical Chemistry (journal) ; Raman scattering ; Quantitative analysis (chemistry) ; Support vector machine ; Noise (video) ; Computer science ; Artificial intelligence ; Chemistry ; Mathematics ; Optics ; Physics ; Chromatography ; Machine learning Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Face and Expression Recognition
Authors: Hao Liang | Meng Zhang | Chao Gao | Yandong Zhao
Source: Sensors (article, 2018-06-18)
Field: Chemistry — Analytical Chemistry

Non-Destructive Methodology to Determine Modulus of Elasticity in Static Bending of Quercus mongolica Using Near-Infrared Spectroscopy This article presents a non-destructive methodology to determine the modulus of elasticity (MOE) in static bending of wood through the use of near-infrared (NIR) spectroscopy. Wood specimens were obtained from <i>Quercus mongolica</i> growing in Northeast of China. The NIR spectra of specimens were acquired by using a one-chip NIR fiber optic spectrometer whose spectral range was 900~1900 nm. The raw spectra of specimens were pretreated by multiplication scatter correlation and Savitzky-Golay smoothing and differentiation filter. To reduce the dimensions of data and complexity of modeling, the synergy interval partial least squares and successive projections algorithm were applied to extract the characteristic wavelengths, which had closing relevance with the MOE of wood, and five characteristic wavelengths were selected from full 117 variables of a spectrum. Taking the characteristic wavelengths as input values, partial least square regression (PLSR) and the propagation neural network (BPNN) were implemented to establish calibration models. The predictive ability of the models was estimated by the coefficient of determination (<i>r<sub>p</sub></i>) and the root mean square error of prediction (RMSEP) and in the prediction set. In comparison with the predicted results of the models, BPNN performed better results with the higher <i>r<sub>p</sub></i> of 0.91 and lower RMSEP of 0.76. The results indicate that it is feasible to accurately determine the MOE of wood by using the NIR spectroscopy technique. Partial least squares regression ; Mean squared error ; Near-infrared spectroscopy ; Smoothing ; Coefficient of determination ; Spectroscopy ; Correlation coefficient ; Mathematics ; Spectrometer ; Calibration ; Materials science ; Elasticity (physics) ; Wavelength ; Analytical Chemistry (journal) ; Biological system ; Optics ; Statistics ; Composite material ; Chemistry ; Physics ; Chromatography Spectroscopy and Chemometric Analyses ; Wood Treatment and Properties ; Wood and Agarwood Research
Authors: Yonghou Xiao | Gaohong He | Mingpu Yuan
Source: Industrial & Engineering Chemistry Research (article, 2018-10-02)
Field: Materials Science — Materials Chemistry

Adsorption Equilibrium and Kinetics of Methanol Vapor on Zeolites NaX, KA, and CaA and Activated Alumina Methanol vapor as a contaminant presented in industrial streams leads to catalysts deactivation. Therefore, it needs deep removal with adsorption technique. The isotherms and effective diffusion coefficients of methanol vapor are essential to design the purification process. The equilibrium sorption of methanol steam on commercial zeolites NaX, KA, and CaA and activated alumina were tested using an intelligent gravimetric analyzer, respectively. The equilibrium experiments were carried out at 303.2 K and pressures of up to 19.6 kPa, and the results obtained were fitted with the Dubinin–Astakhov (D-A) model. Moreover, the diffusion of methanol vapor in the adsorbents was investigated, and the effective diffusion coefficients were obtained with fitting the Fick diffusion model. The adsorbents are compared on the basis of adsorption capacities for methanol steam, and the descending order of zeolites is NaX > CaA > KA > Al2O3. The sorption equilibrium experimental results of methanol steam on NaX, KA, and CaA agree well with D-A isotherm model, while it is not very well consistent on Al2O3. The equilibrium adsorption capacities of methanol vapor are consistent with the effective diffusion coefficients on the adsorbents. Adsorption ; Methanol ; Sorption ; Gravimetric analysis ; Chemistry ; Diffusion ; Activated carbon ; Water vapor ; Thermodynamics ; Chemical engineering ; Physical chemistry ; Organic chemistry Catalytic Processes in Materials Science ; Carbon Dioxide Capture Technologies ; Zeolite Catalysis and Synthesis
Authors: Zvezdelina Yaneva
Source: Chemical and Biochemical Engineering Quarterly (article, 2018-10-14)
Field: Chemistry — Organic Chemistry

Drug Mass Transfer Mechanism, Thermodynamics, and In Vitro Release Kinetics of Antioxidant-encapsulated Zeolite Microparticles as a Drug Carrier System The aim of the present study was to develop a new vitamin E-zeolite drug carrier system, and investigate the mass transfer mechanism of the antioxidant encapsulation and release on/from the mineral matrix by thermodynamic and kinetics sorption/desorption experiments and mathematical modelling of the experimental data. The surface, morphological and spectral characteristics of the vitamin and the zeolite were determined by Boehm titration, SEM, FTIR and UV/Vis spectrophotometric analyses. Intraparticle diffusion was not the only rate-limiting mechanism, as the mixed-order kinetics model gave the highest regression coefficient (R 2 ) and lowest SSE, MSE, RMSE, and AIC C values. The thermodynamic study confirmed the endothermic nature of the spontaneous encapsulation process and increased degrees of randomness at the solid-liquid interface. The in vitro release results were best modelled by the zero-order and sigmoidal models. The results obtained are essential for the development of innovative vitamin E-carrier systems for application in human and veterinary medicine. Chemistry ; Kinetics ; Sorption ; Titration ; Thermodynamics ; Chromatography ; Chemical engineering ; Physical chemistry ; Adsorption Free Radicals and Antioxidants ; Antioxidant Activity and Oxidative Stress ; Protein Interaction Studies and Fluorescence Analysis
Authors: Xiaoxiao Wang | Jaana Vapaavuori | C. Géraldine Bazuin | Christian Pellerin
Source: Macromolecules (article, 2018-01-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Molecular-Level Study of Photoorientation in Hydrogen-Bonded Azopolymer Complexes To optimize azobenzene-containing materials for applications such as rewritable waveguides and holographic data storage, it is imperative to understand the effect of the azobenzene structure on the photoresponse of the material. Supramolecular materials, in which a complexed photoactive azobenzene controls the motion or other properties of a passive polymer, are uniquely convenient for studying the impact of specific chemical modifications. Here, we use polarization modulation infrared structural absorbance spectroscopy (PM-IRSAS) to study hydrogen-bonded supramolecular azobenzene complexes using poly(4-vinylpyridine) (P4VP) as a model polymer. We show that changing the tail group from hydrogen (AH) to cyano (ACN) induces greater angular redistribution of the chromophores and, remarkably, provokes P4VP pyridine ring orientation. Increasing the degree of complexation decreases the saturated orientation of both AH and ACN, whereas for P4VP/ACN it increases the pyridine orientation as well as the orientation stability of both components. These results explain the contrasting photoinduced birefringence behavior previously observed for these complexes and identify azo–azo intermolecular interactions as the main reason. To our knowledge, this is the first molecular-level spectroscopic analysis of the contrasting contributions of azobenzenes to the photoorientation of supramolecular azopolymer complexes and the first report of the large impact of small molecular changes on the capacity of azo dyes to transfer light-induced orientation to a photopassive polymer. Azobenzene ; Supramolecular chemistry ; Chromophore ; Polymer ; Materials science ; Photochemistry ; Supramolecular polymers ; Pyridine ; Hydrogen bond ; Intermolecular force ; Birefringence ; Absorbance ; Polymer chemistry ; Molecule ; Chemistry ; Organic chemistry ; Optics Liquid Crystal Research Advancements ; Photochromic and Fluorescence Chemistry ; Synthesis and Properties of Aromatic Compounds
Authors: Andrés García | Igor I. Slowing | James W. Evans
Source: The Journal of Chemical Physics (article, 2018-07-09)
Field: Materials Science — Materials Chemistry

Pore diameter dependence of catalytic activity: <i>p</i>-nitrobenzaldehyde conversion to an aldol product in amine-functionalized mesoporous silica The reaction yield for conversion of p-nitrobenzaldehyde (PNB) to an aldol product in amine-functionalized mesoporous silica nanoparticles (MSN) exhibits a 20-fold enhancement for a modest increase in pore diameter, d. This enhanced catalytic activity is shown to reflect a strong increase in the "passing propensity," P, of reactant and product species inside the pores. We find that P ≈ 0, corresponding to single-file diffusion, applies for the smallest d which still significantly exceeds the linear dimensions of PNB and the aldol product. However, in this regime of narrow pores, these elongated species must align with each other and with the pore axis in order to pass. Thus, P reflects both translational and rotational diffusion. Langevin simulation accounting for these features is used to determine P versus d. The results are also augmented by analytic theory for small and large d where simulation is inefficient. The connection with the catalytic activity and yield is achieved by the incorporation of results for P into a multi-scale modeling framework. Specifically, we apply a spatially coarse-grained (CG) stochastic model for the overall catalytic reaction-diffusion process in MSN. Pores are treated as linear arrays of cells from the ends of which species adsorb and desorb, and between which species hop and exchange, with the exchange rate reflecting P. CG model predictions including yield are assessed by Kinetic Monte Carlo simulation. Mesoporous silica ; Mesoporous material ; Aldol reaction ; Yield (engineering) ; Diffusion ; Catalysis ; Desorption ; Kinetic Monte Carlo ; MCM-41 ; Materials science ; Amine gas treating ; Chemical engineering ; Chemistry ; Monte Carlo method ; Adsorption ; Physical chemistry ; Thermodynamics ; Organic chemistry ; Composite material ; Physics ; Mathematics Mesoporous Materials and Catalysis ; Catalytic Processes in Materials Science ; Nanomaterials for catalytic reactions
Authors: Mansoor Khan | Mustafa Soylak
Source: Atomic Spectroscopy (article, 2018-04-25)
Field: Chemistry — Analytical Chemistry

Magnetic Solid Phase Extraction of Lead, Cadmium, and Cobalt on Magnetic Carboxyl-Modified Nanodiamonds (MCNDs) from Natural Water Samples and Their Determination by Flame Atomic Absorption Spectrometry A magnetic carboxyl-modified nanodiamond (MCND) was used for the magnetic solid phase extraction of Pb(II), Cd(II), and Co(II) prior to their quantification by flame atomic absorption spectrometry. The external magnetic field was used to separate the magnetic solid phase from the analyte solution in order to avoid sample loss during filtration and centrifugation. Various factors affecting the extraction efficiency of the adsorbent such as solution pH, adsorbent dose, sample volume, temperature, matrix effect, and desorption condition were optimized. The analytical parameters of the limit of detection (Pb: 0.99 g L -1 , Co: 1.73 g L -1 , Cd: 0.15 g L -1 ), preconcentration factor of 20 for the analytes, and percent relative standard deviation (Pb: 0.5%, Cd: 0.6%, Co: 0.6%) were calculated under optimized experimental condition. The kinetic data show that this adsorption process follows pseudo-second order kinetics. The thermodynamic data show that this adsorption process was feasible and exothermic in nature. The method was validated by applying the method to certified reference materials TMDA 64.2 and SPS-WW2 and natural water samples with satisfactory recovery results. Chemistry ; Cadmium ; Cobalt ; Solid phase extraction ; Atomic absorption spectroscopy ; Analytical Chemistry (journal) ; Extraction (chemistry) ; Mass spectrometry ; Phase (matter) ; Inorganic chemistry ; Environmental chemistry ; Chromatography Analytical chemistry methods development ; Electrochemical Analysis and Applications
Authors: Liang‐Yu Chen | Peng Sang | Lina Zhang | Dongpo Song | Yan-Qiu Chu | Linjiang Chai | Lai‐Chang Zhang
Source: Metals (article, 2018-09-25)
Field: Materials Science — Materials Chemistry

Homogenization and Growth Behavior of Second-Phase Particles in a Deformed Zr–Sn–Nb–Fe–Cu–Si–O Alloy Homogeneous distribution of fine second-phase particles (SPPs) fabricated by cycles of deformation and annealing in zirconium alloys is a critical consideration for the corrosion resistance of fuel claddings. Different deformation degrees of zirconium alloys would result in distinctive microstructures, leading to a distinct growth of SPPs during subsequent annealing. Unfortunately, the homogenization and growth behavior of SPPs in deformed zirconium alloys have not been well studied. In this work, a β-quenched Zr–Sn–Nb–Fe–Cu–Si–O alloy was rolled and annealed at 580 °C or 680 °C. The morphologies, distributions, and sizes of SPPs resulting from the different processing procedures were investigated. A linear distribution of SPPs is found in the β-quenched sample. Afterward, SPPs grow and are randomly distributed during heat treatment as the deformation degree or annealing time (or temperature) increases. The homogenization and growth of SPPs are attributed to the Ostwald ripening mechanism that is governed by lattice diffusion and short-circuit diffusion. The sample with a higher deformation degree is speculated to have a larger number of defects that provide more shortcuts for the mass transfer of SPPs, thereby facilitating a homogeneous distribution of fine SPPs during annealing. Annealing (glass) ; Materials science ; Ostwald ripening ; Alloy ; Homogenization (climate) ; Zirconium ; Zirconium alloy ; Homogeneous ; Metallurgy ; Microstructure ; Composite material ; Thermodynamics ; Nanotechnology Nuclear Materials and Properties ; High Temperature Alloys and Creep ; Aluminum Alloy Microstructure Properties
Authors: L.A. Reith | Karla Lienau | Daniel S. Cook | René Moré | Richard I. Walton | Greta R. Patzke
Source: Chemistry - A European Journal (article, 2018-05-23)
Field: Materials Science — Materials Chemistry

Monitoring the Hydrothermal Growth of Cobalt Spinel Water Oxidation Catalysts: From Preparative History to Catalytic Activity The hydrothermal growth of cobalt oxide spinel (Co<sub>3</sub> O<sub>4</sub> ) nanocrystals from cobalt acetate precursors was monitored with in situ powder X-ray diffraction (PXRD) in combination with ex situ electron microscopy and vibrational spectroscopy. Kinetic data from in situ PXRD monitoring were analyzed using Sharp-Hancock and Gualtieri approaches, which both clearly indicate a change of the growth mechanism for reaction temperatures above 185 °C. This mechanistic transition goes hand in hand with morphology changes that notably influence the photocatalytic oxygen evolution activity. Complementary quenching investigations of conventional hydrothermal Co<sub>3</sub> O<sub>4</sub> growth demonstrate that these insights derived from in situ PXRD data provide valuable synthetic guidelines for water oxidation catalyst production. Furthermore, the ex situ analyses of hydrothermal quenching experiments were essential to assess the influence of amorphous cobalt-containing phases arising from the acetate precursor on the catalytic activity. Thereby, the efficient combination of a single in situ technique with ex situ analyses paves the way to optimize parameter-sensitive hydrothermal production processes of key energy materials. Catalysis ; Hydrothermal circulation ; Cobalt ; Powder diffraction ; Cobalt oxide ; Spinel ; Materials science ; Hydrothermal synthesis ; Chemical engineering ; Quenching (fluorescence) ; Amorphous solid ; Inorganic chemistry ; Chemistry ; Crystallography ; Metallurgy ; Organic chemistry Copper-based nanomaterials and applications ; Electrocatalysts for Energy Conversion ; Catalytic Processes in Materials Science