jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Muhammad Alhassan | Shamsuddeen Idris Muazu | Habibu Ahmad Ibrahim
Source: World Journal of Advanced Engineering Technology and Sciences (article, 2023-01-24)
Field: Materials Science — Materials Chemistry

Construction of mathematical equation to predict the densities of BaO - B2O3 - Bi2O3 glass system using the percentage weights of its constituents Glass systems are now a trending topic of research for radiation shielding. It takes time to fabricate the glass and then to measure its density, following which other properties are determined. Some chemicals’ manufacturers write on the chemical containers the health effect of such chemicals if they get contact with eyes or skin and when inhaled. It’s therefore of great importance to devise non experimental technique to study the physical and shielding properties of glass systems. The aim of this work is to construct a mathematical equation capable of reproducing and predicting densities of glasses in the system given by “yBaO - xBi2O3 - (100 – x -y) B2O3”, where (10 ≤ y ≤ 24 wt% and 0 ≤ x ≤ 100 – y) wt%) so, as to avoid the repetitive fabrication of each member of this system and to cut the cost of fabrication and to assure safety from the chemical exposure. We made used of the existing samples to study the nature of the densities in such system and came up with an equation, using which the densities could be reproduced and some others could be predicted by deciding the weight percentages of the constituent chemicals. The formula has a minimum percentage accuracy of 97.4 %. The use of this formula for studying radiation shielding properties of glasses in this system is therefore of great importance. Electromagnetic shielding ; Fabrication ; Measure (data warehouse) ; Work (physics) ; Construct (python library) ; Materials science ; Thermodynamics ; Mathematics ; Computer science ; Applied mathematics ; Composite material ; Physics ; Database Radiation Shielding Materials Analysis ; Advanced X-ray and CT Imaging ; Radiation Dose and Imaging
Authors: Zane G. Long | Jonathan V. Le | Benjamin B. Katz | Belen G. Lopez | E. D. Tenenbaum | Bonnie Semmling | Ryan Schmidt | Felix Grün | Carter T. Butts | Rachel W. Martin
Source: Applications in Plant Sciences (article, 2023-09-01)
Field: Chemistry — Spectroscopy

Spatially resolved detection of small molecules from press‐dried plant tissue using MALDI imaging This work demonstrates applicability of MALDI-MSI to press-dried plant samples without freezing or cryosectioning, setting the stage for spatially resolved molecule identification. Increased mass resolution and inclusion of tandem mass spectrometry are necessary next steps to allow more specific and reliable compound identification. Mass spectrometry imaging ; Mass spectrometry ; Cuticle (hair) ; MALDI imaging ; Biology ; Plant tissue ; Matrix-assisted laser desorption/ionization ; Matrix (chemical analysis) ; Chromatography ; Botany ; Chemistry ; Desorption ; Adsorption Mass Spectrometry Techniques and Applications ; Plant biochemistry and biosynthesis ; Metabolomics and Mass Spectrometry Studies
Authors: Lucas J. dos Santos | Ilka do Amaral Soares | Evaristo C. Biscaia | Frederico W. Tavares
Source: Research Square (preprint, 2023-08-01)
Field: Materials Science — Materials Chemistry

Comparison of 3D-cDFT and GCMC Simulations for Fluid-Structure Analysis in Amorphous Carbon Nanoporous Materials <title>Abstract</title> Investigating fluid behavior in nanoporous materials is essential for gas storage, separation, and catalysis applications. Here, we present a comparison of two computational methods for fluid-structure analysis in amorphous nanoporous carbon materials: three-dimensional (3D) classical Density Functional Theory (cDFT) and Grand Canonical Monte Carlo (GCMC) simulations. We extended our recent development of 3D-cDFT to allow density-profile analysis without symmetry assumptions, enhancing its applicability to a broader range of porous materials. We provide a theoretical overview and discuss the advantages and limitations of each method. Our results highlight the accuracy of both 3D-cDFT and GCMC simulations while emphasizing differences in computational cost, precision, and scope. We also explore the impact of the non-crystalline structure of amorphous carbon nanopores on fluid structure and adsorption isotherms, as well as fluid-fluid and fluid-solid interactions. We offer insights for selecting computational methods in fluid structure analysis of nanoporous materials, guiding future research and optimization in advanced material development for diverse applications. Nanoporous ; Nanopore ; Amorphous solid ; Materials science ; Porosity ; Porous medium ; Carbon fibers ; Nanotechnology ; Chemistry ; Composite material Catalytic Processes in Materials Science ; Mesoporous Materials and Catalysis ; Zeolite Catalysis and Synthesis
Authors: Nóra Kovács | J. Patrick Zobel
Source: ChemRxiv (preprint, 2023-10-03)
Field: Chemistry — Physical and Theoretical Chemistry

Computational Screening of Photodynamics ofTransition-Metal Complexes The design of photoactive compounds is challenging due to the complicated nature that the ensuing photodynamics can assume. The complexity of this problem increases with the size and flexibility of the system, and the challenge becomes especially difficult in the rational design of open-shell transition-metal complexes where many electronic states and nuclear degrees of freedom participate in the excited-state dynamics. The only alternative is then to screen larger numbers of compounds as is done in the present work using computer simulations for a class of near-infrared emitting vanadium(III) complexes. Starting from the mechanism of the known emitter VCl_3(ddpd) (ddpd = N,N'-di\-meth\-yl-N,N'-di\-py\-ri\-di\-ne-2-yl\-py\-ri\-di\-ne-2,6-diamine), we establish design principles including an increase in the ligand-field strength in the complex in order to achieve higher emission quantum yields. Based on these principles, we design a large set of complexes that are tested for larger ligand-field splitting in static quantum chemistry calculations. For the subset of complexes with increased ligand-field splitting, we then perform nonadiabatic dynamics simulations and identify two promising near-infrared emitter with potential similar or increased emission quantum yield compared to the VCl_3(ddpd) reference. An analysis of the mechanisms of all studied complexes reveals individual relaxation pathways for each compound, confirming the difficulty of the identifying useful rational design principles in these photoactive open-shell transition-metal complexes. Quantum yield ; Ligand (biochemistry) ; Rational design ; Ligand field theory ; Excited state ; Chemistry ; Transition metal ; Quantum ; Chemical physics ; Computational chemistry ; Materials science ; Atomic physics ; Nanotechnology ; Physics ; Quantum mechanics ; Fluorescence ; Catalysis Photochemistry and Electron Transfer Studies ; Molecular Junctions and Nanostructures ; Organic Light-Emitting Diodes Research
Authors: Tsukasa Kida | Masatoshi Ohara | Keigo Inamori | Shogo Nagasawa | Shin‐ichi Kihara | Kentaro Taki
Source: Polymers (article, 2023-02-24)
Field: Materials Science — Polymers and Plastics

Real-Time Monitoring of Pellet Plastication in a Full-Flight Screw and Kneading Disk Elements of a Co-Rotating Self-Wiping Twin-Screw Extruder by Acoustic Emission (AE) Sensing The plastication of pellets in a co-rotating twin-screw extruder is a significant concern for product homogeneity and stability in the plastic industry. We developed a sensing technology for pellet plastication in a plastication and melting zone in a self-wiping co-rotating twin-screw extruder. The collapse of the solid part of the pellets emits an elastic wave as an acoustic emission (AE) that is measured on the kneading section of the twin-screw extruder using homo polypropylene pellets. The recorded power of the AE signal was used as an indicator of the molten volume fraction (MVF) in the range of zero (fully solid) to unity (fully melted). MVF decreased with increasing feed rate monotonically in the range of 2-9 kg/h at a screw rotation speed of 150 rotations per minute (rpm) because of the reduction in the residence time of pellets in the extruder. However, the increase in feed rate from 9 to 23 kg/h at 150 rpm resulted in an increase in the MVF as the friction and compaction of pellets caused their melting. The AE sensor could elucidate the pellet's plastication phenomena caused by friction, compaction of pellets, and melt removal in the twin-screw extruder. Pellets ; Plastics extrusion ; Materials science ; Pellet ; Compaction ; Extrusion ; Composite material ; Polypropylene ; Acoustic emission Polymer crystallization and properties ; Mineral Processing and Grinding ; Natural Fiber Reinforced Composites
Authors: Anders Dalhoff Bruhn | Urban Wünsch | Christopher L. Osburn | Jacob C. Rudolph | Colin A. Stedmon
Source: Limnology and Oceanography Methods (article, 2023-06-20)
Field: Chemistry — Analytical Chemistry

Lignin phenol quantification from machine learning‐assisted decomposition of liquid chromatography‐absorbance spectroscopy data Abstract Analysis of lignin in seawater is essential to understanding the fate of terrestrial dissolved organic matter (DOM) in the ocean and its role in the carbon cycle. Lignin is typically quantified by gas or liquid chromatography, coupled with mass spectrometry (GC‐MS or LC‐MS). MS instrumentation can be relatively expensive to purchase and maintain. Here we present an improved approach for quantification of lignin phenols using LC and absorbance detection. The approach applies a modified version of parallel factor analysis (PARAFAC2) to 2 nd derivative absorbance chromatograms. It is capable of isolating individual elution profiles of analytes despite co‐elution and overall improves sensitivity and specificity, compared to manual integration methods. For most lignin phenols, detection limits below 5 nmol L −1 were achieved, which is comparable to MS detection. The reproducibility across all laboratory stages for our reference material showed a relative standard deviation between 1.47% and 16.84% for all 11 lignin phenols. Changing the amount of DOM in the reaction vessel for the oxidation (dissolved organic carbon between 22 and 367 mmol L −1 ), did not significantly affect the final lignin phenol composition. The new method was applied to seawater samples from the Kattegat and Davis Strait. The total concentration of dissolved lignin phenols measured in the two areas was between 4.3–10.1 and 2.1–3.2 nmol L −1 , respectively, which is within the range found by other studies. Comparison with a different oxidation approach and detection method (GC‐MS) gave similar results and underline the potential of LC and absorbance detection for analysis of dissolved lignin with our proposed method. Lignin ; Absorbance ; Phenol ; Chromatography ; Chemistry ; Decomposition ; Spectroscopy ; Organic chemistry ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Metabolomics and Mass Spectrometry Studies
Authors: Nerdy Nerdy | Nilsya Febrika Zebua | TJUT XENA | MAYA KUSUMA | RANI FARAH BUTSAINAH TANJUNG
Source: Jurnal Natural (article, 2023-10-07)
Field: Chemistry — Electrochemistry

The effect of ripeness level, storage and heating conditions on vitamin C in Fig (Ficus carica L.) fruit juice using bivoltammetry sensor Vitamin C, as a crucial nutrient, plays a vital role in human health and is known to be sensitive to various factors such as ripeness level, storage and heating conditions. This study aimed to determine the effect of ripeness level, storage and heating conditions on vitamin C in fig (Ficus carica L.) fruit juice using bivolmetric sensor. Fig (Ficus carica L.) fruit juice samples with different ripeness level were collected and analyzed the vitamin C. Full-ripe fig (Ficus carica L.) fruit juice samples subjected at different storage (cold, cool, and room temperature) and heating (30 °C, 60 °C, and 90 °C) conditions. The vitamin C level was monitored using a bivoltammetry sensor. The results showed that the higher ripeness level of fig (Ficus carica L.) fruit the lower level of the vitamin C. The results also showed that the higher storage and heating conditions generally accelerate with degradation of vitamin C. Degradation of vitamin C content in fig (Ficus carica L.) fruit juice with all different storage temperature had the best kinetic model fit zero order. Meanwhile, heating temperature at 30 °C and 60 °C showed that the best kinetic model fit first order. But, heating temperature at 90 °C showed that the best kinetic model fit second order. The kinetic modeling analysis showed that storage and heating conditions significantly influenced the degradation kinetics of vitamin C in the fig (Ficus carica L.) fruit juice. Carica ; Ficus ; Ripeness ; Vitamin C ; Chemistry ; Food science ; Botany ; Horticulture ; Ripening ; Biology Electrochemical Analysis and Applications ; Vitamin C and Antioxidants Research ; Phytochemistry and biological activities of Ficus species
Authors: Honglin Fang | Xingge Xu | Hualei Zhang | Qiaoyan Sun | Jun Sun
Source: Materials (article, 2023-09-04)
Field: Materials Science — Materials Chemistry

Alloying Effect on Transformation Strain and Martensitic Transformation Temperature of Ti-Based Alloys from Ab Initio Calculations The accurate prediction of alloying effects on the martensitic transition temperature (<i>M</i><sub>s</sub>) is still a big challenge. To investigate the composition-dependent lattice deformation strain and the <i>M</i><sub>s</sub> upon the <i>β</i> to <i>α</i>″ phase transition, we calculate the total energies and transformation strains for two selected Ti-Nb-Al and Ti-Nb-Ta ternaries employing a first-principles method. The adopted approach accurately estimates the alloying effect on lattice strain and the <i>M</i><sub>s</sub> by comparing it with the available measurements. The largest elongation and the largest compression due to the lattice strain occur along ±[011]<i><sub>β</sub></i> and ±[100]<i><sub>β</sub></i>, respectively. As compared to the overestimation of the <i>M</i><sub>s</sub> from existing empirical relationships, an improved <i>M</i><sub>s</sub> estimation can be realized using our proposed empirical relation by associating the measured <i>M</i><sub>s</sub> with the energy difference between the <i>β</i> and <i>α</i>″ phases. There is a satisfactory agreement between the predicted and measured <i>M</i><sub>s</sub>, implying that the proposed empirical relation could accurately describe the coupling alloying effect on <i>M</i><sub>s</sub>. Both Al and Ta strongly decrease the <i>M</i><sub>s</sub>, which is in line with the available observations. A correlation between the <i>M</i><sub>s</sub> and elastic modulus, <i>C</i><sub>44</sub>, is found, implying that elastic moduli may be regarded as a prefactor of composition-dependent <i>M</i><sub>s</sub>. This work sheds deep light on precisely and directly predicting the <i>M</i><sub>s</sub> of Ti-containing alloys from the first-principles method. Materials science ; Diffusionless transformation ; Ab initio ; Martensite ; Thermodynamics ; Lattice (music) ; Lattice constant ; Ab initio quantum chemistry methods ; Modulus ; Condensed matter physics ; Metallurgy ; Composite material ; Chemistry ; Microstructure ; Diffraction ; Physics Titanium Alloys Microstructure and Properties ; Intermetallics and Advanced Alloy Properties ; Metal and Thin Film Mechanics
Authors: Johannes K. Krondorfer | Christian W. Binder | Andreas Hauser
Source: The Journal of Chemical Physics (article, 2023-07-07)
Field: Materials Science — Materials Chemistry

Symmetry- and gradient-enhanced Gaussian process regression for the active learning of potential energy surfaces in porous materials The theoretical investigation of gas adsorption, storage, separation, diffusion, and related transport processes in porous materials relies on a detailed knowledge of the potential energy surface of molecules in a stationary environment. In this article, a new algorithm is presented, specifically developed for gas transport phenomena, which allows for a highly cost-effective determination of molecular potential energy surfaces. It is based on a symmetry-enhanced version of Gaussian process regression with embedded gradient information and employs an active learning strategy to keep the number of single point evaluations as low as possible. The performance of the algorithm is tested for a selection of gas sieving scenarios on porous, N-functionalized graphene and for the intermolecular interaction of CH4 and N2. Porous medium ; Chemical physics ; Gaussian process ; Symmetry (geometry) ; Adsorption ; Porosity ; Diffusion ; Process (computing) ; Statistical physics ; Energy (signal processing) ; Materials science ; Intermolecular force ; Gaussian ; Molecule ; Chemistry ; Computer science ; Physics ; Computational chemistry ; Thermodynamics ; Mathematics ; Physical chemistry ; Quantum mechanics ; Organic chemistry ; Composite material Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Analytical Chemistry and Chromatography
Authors: Alini Dall Cortivo Lange | Diogo Miron | Le ́tícia Lenz Sfair | Elfrides Eva Scherman Schapoval
Source: Drug Analytical Research (article, 2023-07-26)
Field: Chemistry — Analytical Chemistry

Sitagliptin phosphate: isolation and identification of two degradation products formed under acid conditions and determination of in vitro cytotoxicity Sitagliptin phosphate (STG), used for the treatment of type 2 diabetes, is a drug that belongs to a new class called inhibitors of dipeptidyl peptidase IV (DPPIV). It is known to be the first agent of the class approved by the FDA. Currently, many studies describe the determination of STG in plasma and pharmaceutical formulations but there are few studies on the drug stability. Forced degradation studies were conducted to isolate and identify the main degradation products. It was possible to observe the formation of two degradation products (DP1 and DP2) in hydrochloric 2.5M acid at 60°C. The structural characterization by UPLC-UV/MS of the degradation products was important to understand the degradation mechanism of STG under acid conditions. Purified degradation products were tested in vitro for cytotoxicity with a mononuclear cell assay. No cytotoxicity was observed at the concentration range of 10.0–250.0 µg.mL-1. The structural characterization of the degradation products was important to understand the degradation mechanism of STG under acid conditions. Today, there are some resolutions and consensus, national and international, which show the importance of knowing and identifying the degradation products and also to evaluate the cytotoxic potential of these molecules. Degradation (telecommunications) ; Phosphate ; Cytotoxicity ; In vitro ; Chemistry ; Isolation (microbiology) ; Sitagliptin ; Chromatography ; Biochemistry ; Biology ; Microbiology ; Diabetes mellitus ; Endocrinology ; Computer science ; Type 2 diabetes Analytical Methods in Pharmaceuticals ; Pharmaceutical studies and practices ; Pharmacological Effects and Toxicity Studies
Authors: Nicolas Jolly | Yuriel Núñez Fernández | Xavier Waintal
Source: arXiv (Cornell University) (preprint, 2023-08-07)
Field: Materials Science — Materials Chemistry

Tensorized orbitals for computational chemistry Choosing a basis set is the first step of a quantum chemistry calculation and it sets its maximum accuracy. This choice of orbitals is limited by strong technical constraints as one must be able to compute a large number of six dimensional Coulomb integrals from these orbitals. Here we use tensor network techniques to construct representations of orbitals that essentially lift these technical constraints. We show that a large class of orbitals can be put into ``tensorized'' form including the Gaussian orbitals, Slater orbitals, linear combination thereof as well as new orbitals beyond the above. Our method provides a path for building more accurate and more compact basis sets beyond what has been accessible with previous technology. As an illustration, we construct optimized tensorized orbitals and obtain a 85% reduction of the error on the energy of the $H_2$ molecules with respect to a reference double zeta calculation (cc-pvDz) of the same size. Basis set ; Slater-type orbital ; Linear combination of atomic orbitals ; Valence bond theory ; Molecular orbital theory ; Cubic harmonic ; STO-nG basis sets ; Atomic orbital ; Natural bond orbital ; Molecular orbital ; Orbital hybridisation ; Basis (linear algebra) ; Computer science ; Physics ; Quantum mechanics ; Mathematics ; Geometry ; Molecule Machine Learning in Materials Science ; Protein Structure and Dynamics ; Advanced NMR Techniques and Applications
Authors: Mahbuba Islam | Anna Kaczmarek | Magdalena Montowska | Jolanta Tomaszewska‐Gras
Source: Preprints.org (preprint, 2023-07-20)
Field: Chemistry — Analytical Chemistry

Different Chemometric Approaches to Detect Adulteration of Cold‐Pressed Flaxseed oil with Refined Rapeseed Oil Using Differential Scanning Calorimetry Flaxseed oil is one of the best sources of n-3 fatty acids, thus its adulteration with refined oils can lead to a reduction in its nutritional value and overall quality. The purpose of this study was to use the differential scanning calorimetry (DSC) technique to detect adulterations of cold-pressed flaxseed oil with refined rapeseed oil (RP). Based on the melting phase transition curve, parameters such as peak temperature (T), peak height (h), and percentage of area (P) were determined for pure and adulterated flaxseed oils with a RP concentration of 5, 10, 20, 30, 50% (w/w). Significant linear correlations (p ≤ 0.05) between the RP concentration and all DSC parameters were observed, except for h1. In order to assess the usefulness of the DSC technique for detecting adulterations, three chemometric approaches were compared: 1) classification models (Linear Discriminant Analysis, LDA Adaptive Regression Splines, MARS, Support Vector Machine, SVM, Artificial Neural Networks, ANNs); 2) regression models (Multiple Linear Regression, MLR, MARS, SVM, ANNs, PLS) and 3) a combined model of Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). With the LDA model, the highest accuracy of 99.5% in classifying the samples, followed by ANN&amp;amp;gt; SVM &amp;amp;gt; MARS was achieved. Among the regression models, the ANN model showed the highest correlation between observed and predicted values (R= 0.996), while other models showed goodness of fit as following MARS&amp;amp;gt; SVM&amp;amp;gt; MLR. Comparing OPLS-DA and PLS methods, higher values of R2X(cum) =0.986 and Q2 =0.973 were observed with the PLS model than OPLS-DA. These results demonstrate the usefulness of the DSC technique combined with chemometrics for predicting the adulteration of cold-pressed flaxseed oil with refined rapeseed oil. Differential scanning calorimetry ; Linear discriminant analysis ; Linear regression ; Support vector machine ; Partial least squares regression ; Mathematics ; Multivariate adaptive regression splines ; Mars Exploration Program ; Regression analysis ; Rapeseed ; Chemistry ; Artificial intelligence ; Analytical Chemistry (journal) ; Statistics ; Chromatography ; Food science ; Bayesian multivariate linear regression ; Computer science ; Thermodynamics ; Biology ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Metabolomics and Mass Spectrometry Studies