jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Eric Hoar | Thomas C. Shehee | Lindsay E. Roy
Source: ACS Omega (article, 2021-12-29)
Field: Chemistry — Inorganic Chemistry

Impact of Precipitation Parameters on the Specific Surface Area of PuO<sub>2</sub> Controlling the properties of PuO<sub>2</sub> through processing is of vital importance to environmental transport and fate, production of nuclear fuels, nuclear forensic analyses, stockpile stewardship, and storage of nuclear wastes applications. A number of processing conditions have been identified to control final product properties, including specific surface area (SSA), residual carbon content, adsorption of volatile species, morphology, and particle size. In this paper, a novel approach is developed for the prediction of PuO<sub>2</sub> SSA via the synthetic route of Pu(IV) oxalate precipitation followed by calcination. The proposed model utilizes multivariate regression methodology and leave one out formalism to link Savannah River Site (SRS) precipitation and calcination production data to the SSA of the final product. A comparison among the models provides insight into the accuracy and ability to identify variations amongst the processing data. Additionally, the models may also be used to fit new data outside of the parameters explored in a production facility. Finally, the trained model was compared to a similarly trained conventional model form to illustrate the influence of precipitation parameters on the prediction of the final SSA. The models presented here attempt to provide new methods for more accurate prediction of the PuO<sub>2</sub> product properties in a production scale environment for key environmental and nuclear applications. Stockpile ; Environmental science ; Precipitation ; Multivariate statistics ; Calcination ; Process engineering ; Computer science ; Chemistry ; Engineering ; Machine learning ; Meteorology Radioactive element chemistry and processing ; Nuclear Materials and Properties ; Nuclear and radioactivity studies
Authors: Alžbeta Kubincová | Sereina Riniker | Philippe H. Hünenberger
Source: The Journal of Chemical Physics (article, 2021-09-07)
Field: Materials Science — Materials Chemistry

Solvent-scaling as an alternative to coarse-graining in adaptive-resolution simulations: The adaptive solvent-scaling (AdSoS) scheme A new approach termed Adaptive Solvent-Scaling (AdSoS) is introduced for performing simulations of a solute embedded in a fine-grained (FG) solvent region itself surrounded by a coarse-grained (CG) solvent region, with a continuous FG ↔ CG switching of the solvent resolution across a buffer layer. Instead of relying on a distinct CG solvent model, the AdSoS scheme is based on CG models defined by a dimensional scaling of the FG solvent by a factor s, accompanied by an s-dependent modulation of the atomic masses and interaction parameters. The latter changes are designed to achieve an isomorphism between the dynamics of the FG and CG models, and to preserve the dispersive and dielectric solvation properties of the solvent with respect to a solute at FG resolution. This scaling approach offers a number of advantages compared to traditional coarse-graining: (i) the CG parameters are immediately related to those of the FG model (no need to parameterize a distinct CG model); (ii) nearly ideal mixing is expected for CG variants with similar s-values (ideal mixing holding in the limit of identical s-values); (iii) the solvent relaxation timescales should be preserved (no dynamical acceleration typical for coarse-graining); (iv) the graining level N<sub>G</sub> (number of FG molecules represented by one CG molecule) can be chosen arbitrarily (in particular, N<sub>G</sub> = s<sup>3</sup> is not necessarily an integer); and (v) in an adaptive-resolution scheme, this level can be varied continuously as a function of the position (without requiring a bundling mechanism), and this variation occurs at a constant number of particles per molecule (no occurrence of fractional degrees of freedom in the buffer layer). By construction, the AdSoS scheme minimizes the thermodynamic mismatch between the different regions of the adaptive-resolution system, leading to a nearly homogeneous scaled solvent density s<sup>3</sup>ρ. Residual density artifacts in and at the surface of the boundary layer can easily be corrected by means of a grid-based biasing potential constructed in a preliminary pure-solvent simulation. This article introduces the AdSoS scheme and provides an initial application to pure atomic liquids (no solute) with Lennard-Jones plus Coulomb interactions in a slab geometry. Granularity ; Scaling ; Solvation ; Solvent ; Mixing (physics) ; Statistical physics ; Chemistry ; Chemical physics ; Relaxation (psychology) ; Resolution (logic) ; Molecular dynamics ; Materials science ; Physics ; Computational chemistry ; Mathematics ; Computer science ; Quantum mechanics ; Organic chemistry ; Geometry Block Copolymer Self-Assembly ; Theoretical and Computational Physics ; Material Dynamics and Properties
Authors: Yusu Wang | Jonathan J. Denney | Adam A. Corrao | Guanglong Huang | Mojue Zhang | Praveen Soundararajan | David Montiel | Katsuyo Thornton | Peter G. Khalifah
Source: Journal of Crystal Growth (article, 2021-09-01)
Field: Materials Science — Materials Chemistry

Sample environment effects on synchrotron-measured temperature profiles in an approximant of optical floating zone crystal growth Sample (material) ; Temperature gradient ; Synchrotron ; Thermal ; Crystal (programming language) ; Work (physics) ; Crystal growth ; Synchrotron radiation ; Temperature measurement ; Materials science ; Optics ; Chemistry ; Computational physics ; Analytical Chemistry (journal) ; Mechanical engineering ; Computer science ; Thermodynamics ; Meteorology ; Physics ; Crystallography ; Engineering Solidification and crystal growth phenomena ; Phase-change materials and chalcogenides ; X-ray Diffraction in Crystallography
Authors: Yao Liu | Fu Qiao | Shuwen Wang | Runtao Wang | Lele Xu
Source: RSC Advances (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Application of hyperspectral imaging technology for rapid identification of <i>Ruditapes philippinarum</i> contaminated by heavy metals Human beings are confronted with a serious health hazard when ingesting <i>Ruditapes philippinarum</i> contaminated with heavy metals, and thus it is significantly necessary to identify heavy metal contaminated <i>Ruditapes philippinarum</i>. This study investigates the feasibility of hyperspectral imaging to identify heavy metal contamination in <i>Ruditapes philippinarum</i> rapidly. To reduce the effects of noise, four different spectral pretreatments were performed on the original spectra. To select characteristic wavebands for identification, four waveband selection algorithms based on neighbourhood rough set theory were proposed, namely, mutual information, consistency measure, dependency measure, and variable precision. The selected wavebands were input to an extreme learning machine to construct classification models. The results demonstrated that multiplicative scatter correction pretreatment was suitable for <i>Ruditapes philippinarum</i> hyperspectral imaging datasets. The identification models exhibited satisfactory performance to distinguish healthy <i>Ruditapes philippinarum</i> from those contaminated by both individual and multiple heavy metals. The identification results of Cd and Pb contaminated samples were more accurate than those of Cu and Zn contaminated samples. When the number of training samples decreased the identification performance decreased, but not significantly. The results showed that combined with pattern recognition analysis hyperspectral imaging technology can be used to distinguish healthy <i>Ruditapes philippinarum</i> samples from those contaminated by heavy metals, even with only a small number of training samples. This model is suitable for applications in analysing many shellfish rapidly and non-destructively. Ruditapes ; Hyperspectral imaging ; Heavy metals ; Contamination ; Environmental chemistry ; Environmental science ; Chemistry ; Remote sensing ; Geology ; Biology ; Ecology Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Geochemistry and Geologic Mapping
Authors: Oisaemi Uduagele Izevbekhai | Wilson M. Gitari | Nikita Tawanda Tavengwa
Source: South African Journal of Chemistry (article, 2021-01-01)
Field: Materials Science — Biomaterials

Optimization of Silica Extraction from Diatomaceous Earth using the Central Composite Design of Response Surface Methodology ABSTRACT This work evaluated the extraction efficiency of silica from diatomaceous earth (DE) by conventional solvent extraction (CSE) and ultrasound-assisted extraction (UAE) under basic and acidic (HCl) conditions utilizing response surface methodology (RSM). A common statistical model was used to get the best percentage yield and percentage purity using RSM. Experimental parameters such as stirring time, NaOH concentration (for CSE), sonication time, NaOH/HCl concentration, cycle and amplitude (for UAE methods) were optimized using central composite design (CCD). The analytical responses, that is, percentage yield and percentage purity, were analyzed using ANOVA and regression analysis. The linear coefficient of determination, R2, was high and precise. The overall yield and purity were highest for the UAE method under acid condition (pH 1-2, approximately), making it the most effective silica extraction method from DE. For this method, the optimal conditions for extracting Si from DE were 2 h of sonication, 220 mL of 2.82 M HCl as a leaching/extracting medium, 0.524 cycles and 72.6 % of amplitude. Under these conditions, 82 % of silica was yielded with a purity of about 95 %. The experimental results indicate that high-quality silica can be produced from DE in high yield so that DE can be an alternative silica source. Keywords: Diatomaceous earth, silica, response surface methodology, ultrasound-assisted extraction, conventional solvent extraction. Response surface methodology ; Central composite design ; Sonication ; Extraction (chemistry) ; Yield (engineering) ; Chemistry ; Leaching (pedology) ; Silica gel ; Composite number ; Chromatography ; Coefficient of determination ; Solvent ; Analytical Chemistry (journal) ; Materials science ; Composite material ; Mathematics ; Environmental science ; Soil science Clay minerals and soil interactions ; Mesoporous Materials and Catalysis ; Iron oxide chemistry and applications
Authors: Horacio Serna | Wojciech T. Góźdź | Eva G. Noya
Source: International Journal of Molecular Sciences (article, 2021-10-13)
Field: Materials Science — Materials Chemistry

Structural and Dynamical Behaviour of Colloids with Competing Interactions Confined in Slit Pores Systems with short-range attractive and long-range repulsive interactions can form periodic modulated phases at low temperatures, such as cluster-crystal, hexagonal, lamellar and bicontinuous gyroid phases. These periodic microphases should be stable regardless of the physical origin of the interactions. However, they have not yet been experimentally observed in colloidal systems, where, in principle, the interactions can be tuned by modifying the colloidal solution. Our goal is to investigate whether the formation of some of these periodic microphases can be promoted by confinement in narrow slit pores. By performing simulations of a simple model with competing interactions, we find that both the cluster-crystal and lamellar phases can be stable up to higher temperatures than in the bulk system, whereas the hexagonal phase is destabilised at temperatures somewhat lower than in bulk. Besides, we observed that the internal ordering of the lamellar phase can be modified by changing the pore width. Interestingly, for sufficiently wide pores to host three lamellae, there is a range of temperatures for which the two lamellae close to the walls are internally ordered, whereas the one at the centre of the pore remains internally disordered. We also find that particle diffusion under confinement exhibits a complex dependence with the pore width and with the density, obtaining larger and smaller values of the diffusion coefficient than in the corresponding bulk system. Gyroid ; Lamellar structure ; Cluster (spacecraft) ; Chemical physics ; Colloid ; Materials science ; Phase (matter) ; Diffusion ; Range (aeronautics) ; Particle (ecology) ; Condensed matter physics ; Crystallography ; Thermodynamics ; Chemistry ; Physics ; Polymer Material Dynamics and Properties ; Block Copolymer Self-Assembly ; Pickering emulsions and particle stabilization
Authors: Cheng Sheng | Jiao Yang | Yi Ren
Source: arXiv (Cornell University) (preprint, 2021-09-06)
Field: Materials Science — Materials Chemistry

Data-Driven Learning of 3-Point Correlation Functions as Microstructure Representations This paper considers the open challenge of identifying complete, concise, and explainable quantitative microstructure representations for disordered heterogeneous material systems. Completeness and conciseness have been achieved through existing data-driven methods, e.g., deep generative models, which, however, do not provide mathematically explainable latent representations. This study investigates representations composed of three-point correlation functions, which are a special type of spatial convolutions. We show that a variety of microstructures can be characterized by a concise subset of three-point correlations, and the identification of such subsets can be achieved by Bayesian optimization. Lastly, we show that the proposed representation can directly be used to compute material properties based on the effective medium theory. Representation (politics) ; Generative grammar ; Computer science ; Completeness (order theory) ; Point (geometry) ; Variety (cybernetics) ; Correlation ; Generative model ; Function (biology) ; Bayesian probability ; Artificial intelligence ; Correlation function (quantum field theory) ; Theoretical computer science ; Algorithm ; Mathematics ; Mathematical analysis ; Geometry Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Generative Adversarial Networks and Image Synthesis
Authors: Bahareh Behkamal | Mahmoud Naghibzadeh | Mohammad Reza Saberi | Zeinab Amiri‐Tehranizadeh | Andrea Pagnani | Kamal Al Nasr
Source: Biomolecules (article, 2021-11-26)
Field: Materials Science — Materials Chemistry

Three-Dimensional Graph Matching to Identify Secondary Structure Correspondence of Medium-Resolution Cryo-EM Density Maps Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (~4-10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such as α-helices and β-sheets are observable. Consequently, finding the mapping of the secondary structures of the modeled structure (SSEs-A) to the cryo-EM map (SSEs-C) is one of the primary concerns in cryo-EM modeling. To address this issue, this study proposes a novel automatic computational method to identify SSEs correspondence in three-dimensional (3D) space. Initially, through a modeling of the target sequence with the aid of extracting highly reliable features from a generated 3D model and map, the SSEs matching problem is formulated as a 3D vector matching problem. Afterward, the 3D vector matching problem is transformed into a 3D graph matching problem. Finally, a similarity-based voting algorithm combined with the principle of least conflict (PLC) concept is developed to obtain the SSEs correspondence. To evaluate the accuracy of the method, a testing set of 25 experimental and simulated maps with a maximum of 65 SSEs is selected. Comparative studies are also conducted to demonstrate the superiority of the proposed method over some state-of-the-art techniques. The results demonstrate that the method is efficient, robust, and works well in the presence of errors in the predicted secondary structures of the cryo-EM images. Cryo-electron microscopy ; Resolution (logic) ; Matching (statistics) ; Graph ; Algorithm ; Computer science ; Artificial intelligence ; Pattern recognition (psychology) ; Mathematics ; Chemistry ; Theoretical computer science Enzyme Structure and Function ; RNA and protein synthesis mechanisms ; Advanced Electron Microscopy Techniques and Applications
Authors: Siti Nur Amalina Mohamad Sukri | Kamyar Shameli | Sin‐Yeang Teow | Eleen Dayana Mohamed Isa | Mostafa Yusefi | Zatil Izzah Tarmiz
Source: Journal of Research in Nanoscience and Nanotechnology (article, 2021-08-09)
Field: Materials Science — Materials Chemistry

Short Review: Phytofabrication of Zinc Oxide Nanoparticles for Anticancer Applications Zinc oxide nanoparticles (ZnO NPs) are one of the most well-known materials in the field of nanotechnology. Adopting a more environmentally friendly synthesis methods of ZnO NPs have been the focus in the last few decades. Of all green synthesis methods of ZnO NPs, fabrication with the help of plant extracts has been the most popular due to its many benefits. The use of phytofabricated ZnO NPs in anticancer studies has been conducted increasingly over the last decade because of its high inhibition activity against various types of cancerous cells. This short review article will present the current update on the phytofabrication of ZnO NPs in recent years and discuss on their cytotoxicity mechanism against cancer cells. Nanotechnology ; Zinc ; Nanoparticle ; Materials science ; Cytotoxicity ; Environmentally friendly ; Chemistry ; Biology ; Metallurgy ; Biochemistry Nanoparticles: synthesis and applications ; Moringa oleifera research and applications ; Curcumin's Biomedical Applications
Authors: Isaac Temitope Abiola | Sunday Ayoola Oke
Source: Kufa Journal of Engineering (article, 2021-04-01)
Field: Materials Science — Polymers and Plastics

A FUZZY ANALYTIC HIERARCHY MODEL TO APPRAISE WATER ABSORPTION PROCESS PARAMETERS IN COCOA POD HUSK COMPOSITE Water absorption characteristics of composites are crucial to robust composite design with integrity and long service lives. In the literature, scholars have evaluated the water absorption properties of cocoa pod husk composites but reports regarding their uncertainty and imprecision are missing. In this article, cocoa pod husk particulate reinforced composite material was analyzed for uncertainty and imprecision using the fuzzy analytic process to rank and select the important parameters of the water absorption process. Husk ; Absorption of water ; Composite number ; Point of delivery ; Fuzzy logic ; Absorption (acoustics) ; Mathematics ; Materials science ; Composite material ; Environmental science ; Computer science ; Botany ; Artificial intelligence ; Biology Natural Fiber Reinforced Composites ; Textile materials and evaluations ; Nanocomposite Films for Food Packaging
Authors: S. June Oh
Source: Genomics & Informatics (article, 2021-06-30)
Field: Chemistry — Organic Chemistry

Implications of the simple chemical structure of the odorant molecules interacting with the olfactory receptor 1A1 G protein-coupled receptors (GPCRs), including olfactory receptors, account for the largest group of genes in the human genome and occupy a very important position in signaling systems. Although olfactory receptors, which belong to the broader category of GPCRs, play an important role in monitoring the organism's surroundings, their actual three-dimensional structure has not yet been determined. Therefore, the specific details of the molecular interactions between the receptor and the ligand remain unclear. In this report, the interactions between human olfactory receptor 1A1 and its odorant molecules were simulated using computational methods, and we explored how the chemically simple odorant molecules activate the olfactory receptor. G protein-coupled receptor ; Receptor ; Olfactory receptor ; Homology modeling ; Olfaction ; Computational biology ; Biology ; Docking (animal) ; Chemistry ; Neuroscience ; Biochemistry ; Medicine Free Radicals and Antioxidants ; Computational Drug Discovery Methods ; Receptor Mechanisms and Signaling
Authors: Ricardo Rodrigues de Oliveira | Larissa Ferreira Rodrigues Moreira | João Fernando Mari | Murilo Coelho Naldi | Emerson Gomes Milagres | Benedito Rocha Vital | Angélica de Cássia Oliveira Carneiro | Daniel Henrique Breda Binoti | Pablo Falco Lopes | Hélio Garcia Leite
Source: Maderas Ciencia y tecnología (article, 2021-09-01)
Field: Chemistry — Organic Chemistry

Automatic identification of charcoal origin based on deep learning The differentiation between the charcoal produced from (Eucalyptus) plantations and native forests is essential to control, commercialization, and supervision of its production in Brazil. The main contribution of this study is to identify the charcoal origin using macroscopic images and Deep Learning Algorithm. We applied a Convolutional Neural Network (CNN) using VGG-16 architecture, with preprocessing based on contrast enhancement and data augmentation with rotation over the training set images. on the performance of the CNN with fine-tuning using 360 macroscopic charcoal images from the plantation and native forests. The results pointed out that our method provides new perspectives to identify the charcoal origin, achieving results upper 95 % of mean accuracy to classify charcoal from native forests for all compared preprocessing strategies. Charcoal ; Convolutional neural network ; Preprocessor ; Artificial intelligence ; Computer science ; Identification (biology) ; Deep learning ; Pattern recognition (psychology) ; Machine learning ; Chemistry ; Botany Wood and Agarwood Research ; Industrial Vision Systems and Defect Detection ; Currency Recognition and Detection
Authors: Navideh Abbasnezhad | Mohammadali Shirinbayan | Fatiha Chabi | Stéphane Champmartin | Abbas Tcharkhtchi | Farid Bakir
Source: Polymers (article, 2021-08-05)
Field: Materials Science — Polymers and Plastics

Viscoelastic Behavior of Drug-Loaded Polyurethane Drug-eluting stents are desirable platforms for local medicine delivery. However, the incorporation of drugs into polymers can influence the mechanical and physicochemical properties of said matrix, which is a topic that is still poorly understood. In fact, this is more noticeable since the apposition is most often accompanied by mechanical stresses on the polymer coating, which can induce therapeutic failure that can result in death. It is therefore necessary to better understand their behavior by examining their properties in conditions such as those in living beings. We studied polyurethane drug carriers made in-house. Diclofenac epolamine was chosen as a model hydrophilic medicine. We used thermal measurements (DMTA) and tensile tests. The aim was to establish the influence of the loading and release of the drug on the physicochemical properties of this polymer in the presence of a stagnant or circulating fluid medium, phosphate-buffered saline (PBS). For the two PU/drug loadings studied, the effect of the initial drug load was more marked. The free volume fraction and the number of pores in the samples increased with the increasing percent of the drug and with release time. The kinetic profiles were accelerated with the loading ratio and with the presence of flow. Young's modulus and ultimate stress were not significantly influenced by the release time. A relevant relationship between the tensile properties and the viscoelastic behavior of the samples was developed. Our results have implications for optimizing the performance of drug coatings for stents. Viscoelasticity ; Polyurethane ; Materials science ; Composite material ; Drug ; Medicine ; Pharmacology Polymer Nanocomposites and Properties ; Polymer composites and self-healing ; Epoxy Resin Curing Processes