jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jixin Qiao
Source: Molecules (review, 2020-03-24)
Field: Chemistry — Inorganic Chemistry

Dynamic Flow Approaches for Automated Radiochemical Analysis in Environmental, Nuclear and Medical Applications Automated sample processing techniques are desirable in radiochemical analysis for environmental radioactivity monitoring, nuclear emergency preparedness, nuclear waste characterization and management during operation and decommissioning of nuclear facilities, as well as medical isotope production, to achieve fast and cost-effective analysis. Dynamic flow based approaches including flow injection (FI), sequential injection (SI), multi-commuted flow injection (MCFI), multi-syringe flow injection (MSFI), multi-pumping flow system (MPFS), lab-on-valve (LOV) and lab-in-syringe (LIS) techniques have been developed and applied to meet the analytical criteria under different situations. Herein an overall review and discussion on these techniques and methodologies developed for radiochemical separation and measurement of various radionuclides is presented. Different designs of flow systems with combinations of radiochemical separation techniques, such as liquid-liquid extraction (LLE), liquid-liquid microextraction (LLME), solid phase extraction chromatography (SPEC), ion exchange chromatography (IEC), electrochemically modulated separations (EMS), capillary electrophoresis (CE), molecularly imprinted polymer (MIP) separation and online sensing and detection systems, are summarized and reviewed systematically. Flow injection analysis ; Chromatography ; Environmental analysis ; Extraction (chemistry) ; Chemistry ; Nuclear reprocessing ; Process engineering ; Radiochemistry ; Detection limit ; Engineering ; Plutonium Radioactive element chemistry and processing ; Radioactive contamination and transfer ; Analytical chemistry methods development
Authors: M. Michael Denner | Mark H. Fischer | Titus Neupert
Source: Physical Review Research (article, 2020-09-10)
Field: Materials Science — Materials Chemistry

Efficient learning of a one-dimensional density functional theory This work presents a machine learning scheme to free density functional theory that represents the density functional of a one dimensional fermionic system by a neural network, and allows predictions of ground-state energies and density-density correlators of symmetry-breaking and topological phase transitions. Density functional theory ; Scheme (mathematics) ; Work (physics) ; Orbital-free density functional theory ; Computational learning theory ; Phase (matter) ; Time-dependent density functional theory Machine Learning in Materials Science ; Quantum many-body systems ; Topological Materials and Phenomena
Authors: Qiang Zhou | Lei Ding | Yunhua Zhu | Meiying Zhong | Chuchu Yang
Source: Processes (article, 2020-02-27)
Field: Chemistry — Inorganic Chemistry

Process Parameters Optimization of Gallic Acid Removal from Water by MIEX Resin Based on Response Surface Methodology In this work, the response surface methodology was used to optimize the process parameters of gallic acid adsorption on magnetic ion exchange (MIEX) resin. Based on Box-Behnken Design, a quadratic polynomial model equation including solution pH, gallic acid concentration, MIEX resin dosage and adsorption time was established. The reliability of the established regression equation was tested by variance analysis. Based on the regression equation, the technical parameters for gallic acid adsorption on MIEX resin were optimized and the effects of interaction between variables on the removal of gallic acid were analyzed. The results showed that the established regression equation was reliable and could effectively predict the removal of gallic acid. The optimal technical parameters were determined to be a pH of 9.17, a gallic acid concentration of 8.07 mg/L, a resin dosage of 0.98 mL/L and an adsorption time of 46.43 min. The removal efficiency of gallic acid was 97.93% under the optimal parameters. The interaction between pH and adsorption time had the most significant effect on the removal of gallic acid. The results of this study demonstrated that MIEX resin can remove gallic acid efficiently and relatively quickly under the condition of optimal technical parameters. Gallic acid ; Adsorption ; Chemistry ; Chromatography ; Ion-exchange resin ; Response surface methodology ; Inorganic chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Adsorption and biosorption for pollutant removal ; Water Quality Monitoring and Analysis
Authors: Kosuke Ogata | Chih‐Hsiang Chang | Yasushi Ishihama
Source: Mass Spectrometry (article, 2020-12-10)
Field: Chemistry — Spectroscopy

Effect of Phosphorylation on the Collision Cross Sections of Peptide Ions in Ion Mobility Spectrometry The insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups. Phosphopeptide ; Ion-mobility spectrometry ; Peptide ; Phosphoproteomics ; Mass spectrometry ; Ion ; Phosphorylation ; Chemistry ; Proteomics ; Phosphate ; Protein phosphorylation ; Chromatography ; Biochemistry ; Protein kinase A ; Organic chemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Analytical Chemistry and Chromatography
Authors: Ignacio Rubio | Antonio Díaz-Álvarez | R. Bernier | A. Rusinek | J.A. Loya | María Henar Miguélez | Marcos Rodríguez-Millán
Source: Sensors (article, 2020-05-17)
Field: Materials Science — Materials Chemistry

Postmortem Analysis Using Different Sensors and Technologies on Aramid Composites Samples after Ballistic Impact This work focuses on the combination of two complementary non-destructive techniques to analyse the final deformation and internal damage induced in aramid composite plates subjected to ballistic impact. The first analysis device, a 3D scanner, allows digitalising the surface of the tested specimen. Comparing with the initial geometry, the permanent residual deformation (PBFD) can be obtained according to the impact characteristics. This is a significant parameter in armours and shielding design. The second inspection technique is based on computed tomography (CT). It allows analysing the internal state of the impacted sample, being able to detect possible delamination and fibre failure through the specimen thickness. The proposed methodology has been validated with two projectile geometries at different impact velocities, being the reaction force history on the specimen determined with piezoelectric sensors. Different loading states and induced damages were observed according to the projectile type and impact velocity. In order to validate the use of the 3D scanner, a correlation between impact velocity and damage induced in terms of permanent back face deformation has been realised for both projectiles studied. In addition, a comparison of the results obtained through this measurement method and those obtained in similar works, has been performed in the same range of impact energy. The results showed that CT is needed to analyse the internal damage of the aramid sample; however, this is a highly expensive and time-consuming method. The use of 3D scanner and piezoelectric sensors is perfectly complementary with CT and could be relevant to develop numerical models or design armours. Projectile ; Aramid ; Materials science ; Delamination (geology) ; Scanner ; Deformation (meteorology) ; Composite material ; Ballistic impact ; Ballistic limit ; Composite number ; Conical surface ; Fracture (geology) ; Impact ; Work (physics) ; Structural engineering ; Computer science ; Mechanical engineering ; Engineering High-Velocity Impact and Material Behavior ; Energetic Materials and Combustion ; Structural Response to Dynamic Loads
Authors: Anis Sufiya Hamzah | Azlinah Mohamed
Source: IAES International Journal of Artificial Intelligence (review, 2020-12-01)
Field: Chemistry — Analytical Chemistry

Classification of white rice grain quality using ANN: a review Exploring the new method of using technology for classifying rice grain quality is pertinent for rice producers in order to provide quality grains and protect consumers from any contamination exist. This is even more important when in today’s market we can see that rice with low quality is traded without stringent quality control which at the end will affect consumer’s health. This paper will review classification methods in determining quality white rice grain. Although there are many researchers developing new process to do rice classification by using different technique, there are still more advanced technique that can be used to do classification. This paper will focus on classifying rice grain quality using artificial neural network (ANN) approach with the help of image processing to identify the impurities contained in the rice grains. The findings show ANN using BPNN has the highest accuracy of 96%, it is also noted that other methods provide equally better performance. This review indicate hybrid method in ANN should be explored next for future work. White rice ; Computer science ; Quality (philosophy) ; Artificial neural network ; Agricultural engineering ; Grain quality ; Artificial intelligence ; Machine learning ; Pattern recognition (psychology) ; Agronomy ; Food science ; Engineering Spectroscopy and Chemometric Analyses ; Mineral Processing and Grinding
Authors: Zhuowen Zhao | Thomas R. Bieler | Javier LLorca | Philip Eisenlohr
Source: Scripta Materialia (article, 2020-05-11)
Field: Materials Science — Materials Chemistry

Grain boundary slip transfer classification and metric selection with artificial neural networks Artificial neural network ; Slip (aerodynamics) ; Materials science ; Binary number ; Metric (unit) ; Artificial intelligence ; Pattern recognition (psychology) ; Transfer of learning ; Grain boundary ; Biological system ; Computer science ; Algorithm ; Mathematics ; Engineering ; Composite material ; Thermodynamics ; Physics ; Biology Microstructure and mechanical properties ; Metal Forming Simulation Techniques ; Mechanical stress and fatigue analysis
Authors: Kousuke Nakano | Ryo Maezono | Sandro Sorella
Source: Physical review. B./Physical review. B (article, 2020-04-07)
Field: Materials Science — Materials Chemistry

Speeding up <i>ab initio</i> diffusion Monte Carlo simulations by a smart lattice regularization One of the most significant drawbacks of the all-electron ab initio diffusion Monte Carlo (DMC) is that its computational cost drastically increases with the atomic number ($Z$), which typically scales with ${Z}^{\ensuremath{\sim}6}$. In this study, we introduce a very efficient implementation of the lattice regularized diffusion Monte Carlo (LRDMC), where the conventional time discretization is replaced by its lattice space counterpart. This scheme enables us to conveniently adopt a small lattice space in the vicinity of nuclei, and a large one in the valence region, by which a considerable speedup is achieved, especially for large atomic number $Z$. Indeed, the computational performances of the improved LRDMC can be theoretically established based on the Thomas-Fermi model for heavy atoms, implying the optimal ${Z}^{\ensuremath{\sim}5}$ scaling for all-electron DMC calculations. This improvement enables us to apply the DMC technique even for superheavy elements ($Z\ensuremath{\ge}104$), such as oganesson ($Z=118)$, which has the highest atomic number of all synthesized elements so far. Monte Carlo method ; Ab initio ; Diffusion Monte Carlo ; Statistical physics ; Lattice (music) ; Physics ; Speedup ; Quantum Monte Carlo ; Ab initio quantum chemistry methods ; Scaling ; Dynamic Monte Carlo method ; Computational physics ; Monte Carlo molecular modeling ; Quantum mechanics ; Computer science ; Mathematics ; Markov chain Monte Carlo Machine Learning in Materials Science ; Thermal properties of materials ; Electron and X-Ray Spectroscopy Techniques
Authors: A‐Lin Xia | Yu Zhang | Liangzhong Zhao | Pan Qin
Source: Analytical Sciences (article, 2020-09-03)
Field: Chemistry — Analytical Chemistry

Simultaneous, Rapid and Nondestructive Determination of Moisture, Fat Content and Storage Time in Leisure Dried Tofu Using LF-NMR Partial least squares regression ; Chemistry ; Water content ; Moisture ; Shelf life ; Food science ; Nutrient ; Relaxation (psychology) ; Mathematics ; Statistics ; Organic chemistry Spectroscopy and Chemometric Analyses ; NMR spectroscopy and applications ; Polysaccharides Composition and Applications
Authors: H. Fang | Dorte Juul Jensen | Yubin Zhang
Source: Acta Crystallographica Section A Foundations and Advances (article, 2020-09-18)
Field: Materials Science — Materials Chemistry

A flexible and standalone forward simulation model for laboratory X-ray diffraction contrast tomography Laboratory X-ray diffraction contrast tomography (LabDCT) has recently been developed as a powerful technique for non-destructive mapping of grain microstructures in bulk materials. As the grain reconstruction relies on segmentation of diffraction spots, it is essential to understand the physics of the diffraction process and resolve all the spot features in detail. To this aim, a flexible and standalone forward simulation model has been developed to compute the diffraction projections from polycrystalline samples with any crystal structure. The accuracy of the forward simulation model is demonstrated by good agreements in grain orientations, boundary positions and shapes between a virtual input structure and that reconstructed based on the forward simulated diffraction projections of the input structure. Further experimental verification is made by comparisons of diffraction spots between simulations and experiments for a partially recrystallized Al sample, where a satisfactory agreement is found for the spot positions, sizes and intensities. Finally, applications of this model to analyze specific spot features are presented. Diffraction ; Diffraction tomography ; Contrast (vision) ; Optics ; Tomography ; Crystallite ; Segmentation ; Materials science ; Computer science ; Physics ; Artificial intelligence X-ray Diffraction in Crystallography ; Microstructure and mechanical properties ; Advanced X-ray Imaging Techniques
Authors: Qidong Yu | Zhicheng Xu | Jing Zhao | Mindi Zhang | Xiaojian Ma
Source: Micromachines (article, 2020-06-29)
Field: Materials Science — Materials Chemistry

PIV-Based Acoustic Pressure Measurements of a Single Bubble near the Elastic Boundary The objective of this paper was to investigate acoustic pressure waves and the transient flow structure emitted from the single bubble near an elastic boundary based on the particle image velocimetry (PIV). A combination of an electric-spark bubble generator and PIV were used to measure the temporal bubble shapes, transient flow structure, as well as the mid-span deflection of an elastic boundary. Results are presented for three different initial positions near an elastic boundary, which were compared with results obtained using a rigid boundary. A formula relating velocity and pressure was proposed to calculate the acoustic pressure contours surrounding a bubble based on the velocity field of the transient flow structure obtained using PIV. The results show the bubbles near the elastic boundary presented a "mushroom" bubble and an inverted cone bubble. Based on the PIV-measured acoustic pressure contours, a significant pressure difference is found between the elastic boundary and the underside of the bubble, which contributed to the formation of the "mushroom" bubble and inverted cone bubble. Furthermore, the bubbles had opposite migration direction near rigid and elastic boundaries, respectively. In detail, the bubble was repelled away from the elastic boundary and the bubble was attracted by the rigid boundary. The resultant force made up of a Bjerknes force and buoyancy force dominated the migration direction of the bubble. Bubble ; Mechanics ; Buoyancy ; Boundary (topology) ; Physics ; Acoustics ; Optics ; Mathematics Ultrasound and Cavitation Phenomena ; Fluid Dynamics and Mixing ; Fluid Dynamics and Heat Transfer
Authors: M.V. Chepak-Gizbrekht | A. G. Knyazeva
Source: Computational Materials Science (article, 2020-07-01)
Field: Materials Science — Materials Chemistry

Grain-boundary diffusion modeling in a microstructural material Triple junction ; Effective diffusion coefficient ; Grain boundary diffusion coefficient ; Diffusion ; Grain boundary ; Materials science ; Phase (matter) ; Amorphous solid ; Thermodynamics ; Molecular dynamics ; Boundary (topology) ; Grain size ; Condensed matter physics ; Chemical physics ; Microstructure ; Crystallography ; Chemistry ; Composite material ; Physics ; Computational chemistry ; Mathematics ; Mathematical analysis Microstructure and mechanical properties ; Aluminum Alloys Composites Properties ; Solidification and crystal growth phenomena
Authors: С.А. Чижик | С. Ф. Бычков | Bogdan V. Voloshin | М. П. Попов | A. P. Nemudry
Source: Chemical Engineering Journal (article, 2020-11-13)
Field: Materials Science — Materials Chemistry

Development of the Crank’s diffusion model for the case of material-gas feedback regime in gas flow reactors. Advanced methodology of oxygen partial pressure relaxation for the kinetics of oxygen exchange in nonstoichiometric oxides Thermodynamics ; Diffusion ; Chemistry ; Oxygen ; Flow (mathematics) ; Partial pressure ; Continuous stirred-tank reactor ; Work (physics) ; Mass transfer ; Mechanics ; Physical chemistry ; Physics Advancements in Solid Oxide Fuel Cells ; Catalysis and Oxidation Reactions ; Electronic and Structural Properties of Oxides
Authors: Yuming Gu | Ziteng Liu | Changzhou Yu | Xu Gu | Lili Xu | Yang Gao | Jing Ma
Source: The Journal of Physical Chemistry C (article, 2020-04-07)
Field: Chemistry — Inorganic Chemistry

Zeolite Adsorption Isotherms Predicted by Pore Channel and Local Environmental Descriptors: Feature Learning on DFT Binding Strength Fast prediction of adsorption isotherms is of great importance in the structural characterization and property prediction of zeolites prior to the synthesis of the target zeolite. Here, we employ the feature learning (FL) method to simulate the adsorption isotherms through density functional theory data generation of binding strength of nitrogen molecule adsorption in zeolites. Three features, that is, the size of adsorption cavities, the geometry of the pore apertures, and the local geometric distortion, are identified to control the binding strength, qualitatively in terms of a polynomial generative model. The local distortion of the Si–O–Si linkage is correlated with the electrostatic polarization of the nitrogen molecule upon adsorption in the zeolite cage. The electrostatic polarization from local zeolite environment can be further adjusted by the Si/Al ratios and thus can enhance the binding strength even twice as the silicalite zeolites when Si/Al = 47. The predicted adsorption isotherms of MFI and MWW zeolites from the feature-learned binding energies are in qualitative agreement with the experimental Brunauer–Emmett–Teller detection data. For 200,429 zeolites, including 248 known zeolites reported in the International Zeolite Association (IZA), the predicted adsorption isotherms are classified into three groups, among which the zeolites with the medium-sized three-dimensional channel architectures are favorable for nitrogen adsorption. The proposed FL scheme is a practical tool to give a quick prediction of adsorption isotherms and high-throughput screening of porous materials for adsorption-related applications. Zeolite ; Adsorption ; Molecule ; Polarization (electrochemistry) ; Chemistry ; Materials science ; Computational chemistry ; Inorganic chemistry ; Chemical engineering ; Physical chemistry ; Organic chemistry ; Catalysis Zeolite Catalysis and Synthesis ; Metal-Organic Frameworks: Synthesis and Applications ; Catalytic Processes in Materials Science
Authors: José E. Mosquera | María L. Goñi | Raquel E. Martini | Nicolás A. Gañán
Source: The Journal of Supercritical Fluids (article, 2020-08-23)
Field: Materials Science — Polymers and Plastics

Mass transfer kinetics of CO2 and eugenol in the supercritical impregnation of polyamide fibers: Experimental data and modeling Differential scanning calorimetry ; Supercritical fluid ; Sorption ; Mass transfer ; Eugenol ; Diffusion ; Crystallinity ; Kinetics ; Materials science ; Context (archaeology) ; Chemical engineering ; Chemistry ; Thermodynamics ; Composite material ; Chromatography ; Organic chemistry ; Adsorption Polymer Foaming and Composites ; Carbon dioxide utilization in catalysis ; Polymer crystallization and properties
Authors: Sandeep Police | Sukanta Maity | Dilip Kumar Chaudhary | Sanjay Kumar Sahu | A. Kumar
Source: Applied Water Science (article, 2020-09-11)
Field: Chemistry — Inorganic Chemistry

An investigation on the efficiency of low-cost adsorbents in removing uranium from water samples Abstract The groundwater samples were found to be contaminated with high concentrations of uranium (U) in Punjab state as well as in few other locations of India. U being chemically toxic can deteriorate health when ingested. Hence, there is a need to remove U from contaminated water using an efficient, cheap and user friendly method. A study was initiated to investigate the efficiency of low-cost adsorbents in removing U from water. Seven adsorbents were screened for U removal efficiency, among which fly ash (FA) and tea waste (TW) were found to have better removal efficiency. Solid–liquid contact time and solution pH were optimized to establish conditions for better U removal efficiency. The U adsorption on FA and TW followed pseudo-second-order kinetics with rate constant values 4.63 g/mg/min and 15.63 g/mg/min, respectively. FA and TW had the highest U removal capability at pH 6 and pH 4, respectively. The U sorption data were fitted with Freundlich and Dubinin–Radushkevich isotherm models. The U adsorption on FA and TW is found to be a physical process with mean free energy ( E ) values less than 8 kJ/mol. Theoretically calculated maximum adsorption capacity values indicate that FA is a better adsorbent as compared to TW, which has been further confirmed experimentally. The U adsorption on both the adsorbents has interference from Ca 2+ and no interference from Fe 3+ at tested U concentrations. It is also found that FA and TW are effective in decontaminating U from spiked real groundwater samples to below the WHO (Guidelines for drinking water quality, 4th ed, vol 1, World Health Organization, Geneva, 2011) limit. Adsorption ; Freundlich equation ; Uranium ; Chemistry ; Sorption ; Human decontamination ; Fly ash ; Nuclear chemistry ; Wastewater ; Chromatography ; Environmental chemistry ; Environmental engineering ; Waste management ; Materials science ; Environmental science ; Metallurgy ; Organic chemistry Radioactive element chemistry and processing ; Radioactivity and Radon Measurements ; Groundwater and Isotope Geochemistry