jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ayşe KURT | Taner Yonar
Source: Scientific Reports (article, 2022-08-18)
Field: Chemistry — Electrochemistry

The evaluation of parameter effects on cefoperazone treatability with new generation anodes In this study it was aimed to investigate the treatability of cefoperazone with new generation Sb-doped SnO<sub>2</sub>-Ni anodes. For this purpose, it was studied with Sn/Sb/Ni: 500/8/1 anodes for the oxidation of aqueous solution containing cefoperazone antibiotic by addition of different types of electrolyte. Potassium chloride was found as the best electrolyte type affecting the electrochemical reactions positively even at lower concentrations (750 mg/L<sup>-1</sup>). At pH 8 the best results were obtained, which is the neutral pH value of the aqueous solution. 50 mA/cm<sup>2</sup> was found as the best value for current density parameter, providing full mineralization just after 60 min of reaction. The removal efficiencies increased generally with the increase of current density, because active oxidants occur increasingly at higher current values. According to the results of the study it was seen that, electrochemical oxidation processes with Sn/Sb/Ni-Ti anodes could be carried out efficiently without need adding extra electrolyte (salt) and pH adjustment step for real wastewaters containing antibiotics. Thus, it was found an easy and economic way to perform electrochemical oxidation with Sn/Sb/Ni-Ti anodes for the wastewaters containing cefoperazone antibiotics. Electrolyte ; Anode ; Electrochemistry ; Supporting electrolyte ; Aqueous solution ; Cefoperazone ; Chemistry ; Chloride ; Mineralization (soil science) ; Salt (chemistry) ; Inorganic chemistry ; Nuclear chemistry ; Antibiotics ; Electrode ; Organic chemistry ; Biochemistry ; Antibiotic resistance Electrochemical Analysis and Applications ; Advanced oxidation water treatment ; Pharmaceutical and Antibiotic Environmental Impacts
Authors: Turakhasanov Isfandior | Nizomov Ziyovuddin | Dilshod Nematov
Source: Trends in Sciences (article, 2022-11-19)
Field: Materials Science — General Materials Science

Effect of the Size of A5N Cylindrical Aluminum Specimens on the Cooling Kinetics The results of the study of “The influence of the size of cylindrical samples of A5N aluminum on the time and the rate of their cooling” are reported. According to experimental data, the temperature dependence of the heat transfer coefficient for pure metals is calculated. It has revealed that the process of cooling of the aluminum and its alloys has a relaxation behavior. It was found that the main mechanisms of natural air cooling are convection heat transfer and radiation. The characteristic cooling time due to radiation is less due to convection. The contribution of thermal radiation is noticeable at high temperatures. It was found that the characteristic times of cooling due to radiation and convection increase with increase in volume to area ratio of the sample. HIGHLIGHTS Cylindrical Al samples were made with dimensions of 2, 2.5, 3, 3.5 and 4 cm, after cleaning aluminum to grade A5N (99.999 %) The influence of the dimensions of cylindrical aluminum samples on the time and rate of their spontaneous cooling in air has been studied It has been established that the samples are cooled mainly due to convective heat transfer and thermal radiation It became known that the cooling time due to convection is longer than the time due to radiation It has been found that as the V/S value increases, the cooling time increases GRAPHICAL ABSTRACT Convection ; Materials science ; Aluminium ; Radiation ; Heat transfer ; Convective heat transfer ; Thermal ; Heat transfer coefficient ; Thermodynamics ; Natural convection ; Thermal radiation ; Air cooling ; Mechanics ; Composite material ; Optics ; Physics Material Properties and Applications ; Heat Transfer and Mathematical Modeling ; Aluminum Alloy Microstructure Properties
Authors: Carlos Ocampo-López | Álvaro Ospina-Sanjuan | Margarita Ramírez-Carmona | Leidy Rendón-Castrillón
Source: Metals (article, 2022-08-28)
Field: Materials Science — Materials Chemistry

Development of a Model to Estimate the Thermodynamic Stability of Organic Substances in Leaching Processes The leaching processes for metals using organic substances represent a sustainable approach to recover precious minerals from solid matrices. However, the generation of organometallic species and the lack of thermodynamic diagrams make it difficult to advance the understanding of their behavior and optimize the process. In this work, a thermodynamically and stoichiometrically consistent mathematical model was developed to estimate the thermodynamic stability of organic substances during the leaching process, and iron leaching with oxalic acid was used as a case study. The Pourbaix and the global thermodynamic stability diagrams for the system were developed in this study. Using a Gaussian®, it was estimated that the Gibbs free energy formation for Fe(C2O4)22−, Fe(C2O4)21−, and Fe(C2O4)33− was −1407.51, −2308.38, and −3068.89 kcal/mol. A set of eleven independent reactions was formulated for the sixteen species involved in the leaching process, and its stability functions in terms of Eh and pH were calculated to generate a 3D global thermodynamic stability diagram. According to the Eh-pH diagrams for the leaching process, ferrioxalate was identified as the most stable and predominant species in the leaching process at pH above 6.6 under reductive conditions. The mathematical model developed in this work resulted in a thermodynamic tool for predicting leaching processes. Leaching (pedology) ; Pourbaix diagram ; Gibbs free energy ; Chemical stability ; Chemistry ; Thermodynamics ; Organic chemistry ; Physical chemistry ; Soil science ; Environmental science Thermal and Kinetic Analysis ; Extraction and Separation Processes ; Chemical and Physical Properties in Aqueous Solutions
Authors: Christian W. Binder | Johannes K. Krondorfer | Andreas Hauser
Source: Molecular Systems Design & Engineering (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

The ridge integration method and its application to molecular sieving, demonstrated for gas purification <i>via</i> graphdiyne membranes A method for the effective calculation of transmission probabilities for processes of molecular sieving is presented and tested against Eyring theory by comparison to Molecular Dynamics simulations. Membrane ; Ridge ; Materials science ; Chemical engineering ; Chromatography ; Chemistry ; Nanotechnology ; Engineering ; Geology ; Biochemistry ; Paleontology Graphene research and applications ; Membrane Separation and Gas Transport ; Molecular Junctions and Nanostructures
Authors: Wenjuan Yu | Jiale Yang | Bingting Wang | Xiang Fu | Changhai Zhou | Haijun Zhou | Guoxiong Xie | Kexiu Dong | Gan Jin
Source: Preprints.org (preprint, 2022-05-06)
Field: Materials Science — Polymers and Plastics

Performance Improvement of PCDTBT: PC70BM Polymer Solar Cells with 1,8-diiodooctane Solvent Additive The power conversion efficiency (PCE) of polymer solar cells (PSCs) are strongly depended on the bulk-heterojunction active layer. Here, the 1,8-diiodooctane (DIO) additives have been added into the PCDTBT: PC70BM blend PSCs. Based on the higher boiling point than host solvent ODB and better solubility of PC71BM, the device photovoltaic properties with DIO additive were changed obviously. The investigations of EQE indicate that the DIO can influence the charge recombination and transportation process, and absorption studies demonstrate that the charge carriers generation process can also be affected by DIO. The overall impact reflected on the decreased equivalent resistant. With 3% v/v DIO, the Jsc, Voc and FF are both increased. Correspondingly, a highest PCE is achieved of 6.15%, while the reference device without DIO only has a PCE of 5.23%. Hence, adding DIO solvent additive is a effective method for the photovoltaic properties improving of PCDTBT: PC70BM blend PSCs. Polymer solar cell ; Materials science ; Energy conversion efficiency ; Active layer ; Photovoltaic system ; Solvent ; Solubility ; Boiling point ; Chemical engineering ; Organic solar cell ; Absorption (acoustics) ; Polymer ; Optoelectronics ; Nanotechnology ; Layer (electronics) ; Organic chemistry ; Composite material ; Chemistry Conducting polymers and applications ; Organic Electronics and Photovoltaics ; Advanced Sensor and Energy Harvesting Materials
Authors: Antonio David Abreu Rejón | Wilberth Antonio Herrera Kao | Alejandro May Pat | Alejandro Ávila‐Ortega | Nayeli Rodríguez Fuentes | Jorge Alonso Uribe Calderón | José Manuel Cervantes‐Uc
Source: Preprints.org (preprint, 2022-09-23)
Field: Materials Science — Surfaces, Coatings and Films

Influence of Molecular Weight and Grafting Density of PEG on the Surface Properties of Polyurethanes and Their Effect on the Viability and Morphology of Fibroblasts and Osteoblasts Grafting polyethylene glycol (PEG) on polymers surface is widely used to improve biocompatibility by reducing protein and cell adhesion. Although PEG is considered to be bioinert, its incorporation to biomaterials has shown to improve cell viability depending on the amount and molecular weight (MW) used. This phenomenon was studied here by grafting PEG of three MW onto polyurethane (PU) substrata at three molar concentrations to assess their effect on PU surface properties and on the viability of osteoblasts and fibroblasts. PEG formed a covering on the substrata which increased the hydrophilicity and surface energy of PUs. Among the results it was observed that osteoblast viability increased for all MW and grafting densities of PEG employed compared with unmodified PU. However, fibroblast viability only increased at certain combinations of MW and grafting densities of PEG, suggesting an optimal level of these parameters. PEG grafting also promoted a more spread cell morphology than that exhibited by unmodified PU; nevertheless, cells became apoptotic-like as PEG MW and grafting density were increased. These effects on cells could be due to PEG affecting culture medium pH, which became more alkaline at higher MW and concentrations of PEG. Results support the hypothesis that surface energy of PU substrates can be tuned by controlling the MW and grafting density of PEG, but these parameters should be optimized to promote cell viability without inducing apoptotic-like behavior. PEG ratio ; Grafting ; Viability assay ; Polyethylene glycol ; Biocompatibility ; Polyurethane ; Biophysics ; Chemical engineering ; Materials science ; Polymer chemistry ; Surface energy ; Morphology (biology) ; Osteoblast ; Polymer ; Cell adhesion ; Adhesion ; Chemistry ; Cell ; Composite material ; Organic chemistry ; Biochemistry ; In vitro ; Biology Polymer Surface Interaction Studies ; Electrospun Nanofibers in Biomedical Applications ; biodegradable polymer synthesis and properties
Authors: Benjamin T. Boyle | Jeffrey N. Levy | Louis de Lescure | Robert S. Paton | Andrew McNally
Source: ChemRxiv (preprint, 2022-07-11)
Field: Chemistry — Organic Chemistry

3-Selective Halogenation of Pyridines via Zincke Imine Intermediates Pyridine halogenation reactions are crucial for obtaining the vast array of derivatives required for drug and agrochemical development. Yet, despite more than a century of synthetic endeavors, there are no broadly applicable 3-selective halogenation processes that function directly from pyridine C–H precursors. We have developed a ring-opening, halogenation, ring-closing sequence that temporarily transforms pyridines into a reactive series of alkenes. These Zincke imine intermediates undergo highly regioselective halogenation reactions under mild conditions. Experimental and computational mechanistic studies indicate that the selectivity-determining step changes based on the halogen electrophile. Using this method, we formed a diverse set of 3-halopyridines and demonstrated late-stage halogenation of complex pharmaceuticals and agrochemicals. Halogenation ; Chemistry ; Electrophile ; Regioselectivity ; Imine ; Pyridine ; Ring (chemistry) ; Halogen ; Selectivity ; Combinatorial chemistry ; Organic chemistry ; Catalysis Catalytic C–H Functionalization Methods ; Advanced Synthetic Organic Chemistry ; Synthesis and Catalytic Reactions
Authors: Swarnava Ghosh
Source: Applied Mechanics (article, 2022-08-24)
Field: Materials Science — Materials Chemistry

Towards Ab-Initio Simulations of Crystalline Defects at the Exascale Using Spectral Quadrature Density Functional Theory Defects in crystalline solids play a crucial role in determining properties of materials at the nano, meso- and macroscales, such as the coalescence of vacancies at the nanoscale to form voids and prismatic dislocation loops or diffusion and segregation of solutes to nucleate precipitates, phase transitions in magnetic materials via disorder and doping. First principles Density Functional Theory (DFT) simulations can provide a detailed understanding of these phenomena. However, the number of atoms needed to correctly simulate these systems is often beyond the reach of many widely used DFT codes. The aim of this article is to discuss recent advances in first principles modeling of crystal defects using the spectral quadrature method. The spectral quadrature method is linear scaling with respect to the number of atoms, permits spatial coarse-graining, and is capable of simulating non-periodic systems embedded in a bulk environment, which allows the application of appropriate boundary conditions for simulations of crystalline defects. In this article, we discuss the state-of-the-art in ab-initio modeling of large metallic systems of the order of several thousand atoms that are suitable for utilizing exascale computing resourses. Density functional theory ; Materials science ; Coalescence (physics) ; Nucleation ; Ab initio ; Periodic boundary conditions ; Granularity ; Nanoscopic scale ; Scaling ; Statistical physics ; Condensed matter physics ; Chemical physics ; Physics ; Boundary value problem ; Nanotechnology ; Computer science ; Thermodynamics ; Quantum mechanics Microstructure and mechanical properties ; Surface and Thin Film Phenomena ; Composite Material Mechanics
Authors: Zhiyong Zou | Qingsong Wu | Jian Wang | Lijia Xu | Man Zhou | Zhiwei Lu | Yong He | Yuchao Wang | Liu Bi | Yongpeng Zhao
Source: Research Square (preprint, 2022-05-11)
Field: Chemistry — Analytical Chemistry

Research on non-destructive testing of hotpot oil quality by Fluorescence Hyperspectral Technology combined with machine learning <title>Abstract</title> Eating repeatedly used hotpot oil will cause serious harm to human health. In order to realize rapid non-destructive testing of hotpot oil quality, a modeling experiment method of fluorescence hyperspectral technology combined with machine learning algorithm was proposed. Five preprocessing algorithms are used to preprocess the original spectral data, which realizes data denoising and reduces the influence of baseline drift and tilt. The characteristic bands extracted from the spectral data show that the best characteristic bands for the two-classification model and the six-classification model are concentrated between 469–962 nm and 534–809 nm, respectively. Using the PCA algorithm to visualize the spectral data, the results show the distribution of the six types of samples intuitively, and indicate that the data can be classified. Based on the modeling analysis of the characteristic bands, the results show that the best two-classification models and the best six-classification models are MF-RF-RF and MF-XGBoost-LGB models, respectively, and the classification accuracy reaches 100%. Compared with the traditional model, the error is greatly reduced, and the calculation time is also saved. This study confirms that the use of fluorescence hyperspectral technology combined with machine learning algorithms provides a new theory and method for hotpot oil quality detection. Hyperspectral imaging ; Preprocessor ; Artificial intelligence ; Data pre-processing ; Computer science ; Pattern recognition (psychology) ; Quality (philosophy) ; Machine learning ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis
Authors: Jung Soo Lee | Y.B. Chun | Won‐Seok Ko
Source: Materials (article, 2022-07-22)
Field: Materials Science — Materials Chemistry

Molecular Dynamics Simulations of PtTi High-Temperature Shape Memory Alloys Based on a Modified Embedded-Atom Method Interatomic Potential A new second nearest-neighbor modified embedded-atom model-based PtTi binary interatomic potential was developed by improving the pure Pt unary descriptions of the pre-existing interatomic potential. Specifically, the interatomic potential was developed focusing on the shape memory-associated phenomena and the properties of equiatomic PtTi, which has potential applications as a high-temperature shape memory alloy. The simulations using the developed interatomic potential reproduced the physical properties of the equiatomic PtTi and various intermetallic compound/alloy compositions and structures. Large-scale molecular dynamic simulations of single crystalline and nanocrystalline configurations were performed to examine the temperature- and stress-induced martensitic transformations. The results show good consistency with the experiments and demonstrate the reversible phase transformation of PtTi SMA between the cubic B2 austenite and the orthorhombic B19 martensite phases. In addition, the importance of anisotropy, constraint and the orientation of grains on the transformation temperature, mechanical response, and microstructure of SMA are presented. Shape-memory alloy ; Materials science ; Embedded atom model ; Interatomic potential ; Molecular dynamics ; Intermetallic ; Austenite ; Martensite ; Nanocrystalline material ; Orthorhombic crystal system ; Atom (system on chip) ; Nickel titanium ; Diffusionless transformation ; Thermodynamics ; Alloy ; Microstructure ; Crystallography ; Metallurgy ; Crystal structure ; Computational chemistry ; Nanotechnology ; Chemistry ; Physics Shape Memory Alloy Transformations ; Titanium Alloys Microstructure and Properties ; Machine Learning in Materials Science
Authors: Nicholas Ho | John Kevin Cava | John Vant | Ankita Shukla | Jake Miratsky | Pavan Turaga | Ross Maciejewski | Abhishek Singharoy
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-10-05)
Field: Materials Science — Materials Chemistry

Learning Free Energy Pathways through Reinforcement Learning of Adaptive Steered Molecular Dynamics Abstract In this paper, we develop a formulation to utilize reinforcement learning and sampling-based robotics planning to derive low free energy transition pathways between two known states. Our formulation uses Jarzynski’s equality and the stiffspring approximation to obtain point estimates of energy, and construct an informed path search with atomistic resolution. At the core of this framework, is our first ever attempt we use a policy driven adaptive steered molecular dynamics (SMD) to control our molecular dynamics simulations. We show that both the reinforcement learning and robotics planning realization of the RL-guided framework can solve for pathways on toy analytical surfaces and alanine dipeptide. Reinforcement learning ; Robotics ; Artificial intelligence ; Realization (probability) ; Computer science ; Energy (signal processing) ; Molecular dynamics ; Robot ; Mathematics ; Physics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Force Microscopy Techniques and Applications
Authors: James W. E. Drewitt | Geoffrey Bromiley
Source: Frontiers in Earth Science (article, 2022-04-26)
Field: Materials Science — Ceramics and Composites

Boron Incorporation in Silicate Melt: Pressure-induced Coordination Changes and Implications for B Isotope Fractionation Ab initio molecular dynamics simulations have been employed to investigate the nature of boron incorporation in a haplobasalt melt at pressures up to 8 GPa. At ambient pressure, boron is predominantly incorporated as trigonal planar BO 3 units. With increasing pressure, the proportion of tetrahedral BO 4 increases markedly in parallel with increases in the coordination of other cations in silicate liquids. In contrast to studies of high-pressure boron-rich silicate glasses and liquids where boron units are polymerized, simulations of low B-concentration liquid here indicate that boron does not adopt a significant role as a network-forming cation. Marked changes in the proportion of BO 4 in silicate melt at even moderate pressures (from 5 to 20%, over the pressure range 0–3 GPa) imply that pressure may significantly affect the extent of melt/fluid and melt/crystal boron isotope fractionation. This pressure-effect should be considered when using boron isotope data to elucidate processes occurring within the mantle. Boron ; Silicate ; Isotopes of boron ; Fractionation ; Mantle (geology) ; Materials science ; Isotope fractionation ; Analytical Chemistry (journal) ; Mineralogy ; Inorganic chemistry ; Geology ; Chemistry ; Geochemistry ; Organic chemistry Glass properties and applications ; High-pressure geophysics and materials ; Geological and Geochemical Analysis
Authors: Jeremy G. Frey
Source: Chemistry International (article, 2022-04-01)
Field: Materials Science — Materials Chemistry

Artificial Intelligence and Chemistry Abstract Following the 100 Year Anniversary of IUPAC celebrated in Paris in 2019, Artificial Intelligence was made the focus of the following global 2021 World Chemistry Leadership Meeting (WCLM). Note: The program of WCLM 2021 is available online. A detailed account of WCLM2021 will follow in the next issue of Chem Int. at https://iupac.org/event/wclm2021/ . Once it was clear the prevailing COVID-19 conditions would mean that the 2021 WCLM would be virtual, the planning committee decided to take advantage of an online setting to have a truly global meeting and to have the event follow the sun round the world using three time zones and “visiting” the next two IUPAC Congress sites, i.e. The Netherlands 2023 and Malaysia 2025. Chemical nomenclature ; Coronavirus disease 2019 (COVID-19) ; Event (particle physics) ; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ; 2019-20 coronavirus outbreak ; Library science ; Operations research ; Chemistry ; Political science ; Engineering ; Computer science ; Physics ; Medicine ; Organic chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; History and advancements in chemistry
Authors: Xuliang Qian | Matteo Andrea Lucherelli | Céline Corcelle | Alberto Bianco | Huajian Gao
Source: Forces in Mechanics (article, 2022-05-14)
Field: Materials Science — Materials Chemistry

Mechanics of biosurfactant aided liquid phase exfoliation of 2D materials Biosurfactant-aided liquid-phase exfoliation (LPE) is emerging as a biocompatible, green, economical, safe, and efficient approach to prepare two-dimensional (2D) materials for biomedical applications. However, relatively little is known about the molecular mechanisms of this process. Herein, we present the first study of how flavin mononucleotide (FMN) interacts with hexagonal boron nitride (hBN) nanosheets in the context of LPE. We demonstrate that FMN molecules can self-assemble on hBN via π-π interactions, as well as intermolecular hydrogen bonds (H-bonds) between the isoalloxazine moieties. Binding free energy analysis has shown FMN to be an efficient surfactant for LPE of hBN in water. According to the theoretical simulations, stable water suspension of hBN were experimentally obtained by LPE using FMN. With this work, we aim to exemplify how molecular dynamics (MD) simulation can predict and guide empirical LPE experiments, direct the surfactant screening and improve scalable production of 2D materials for biomedical applications. Exfoliation joint ; Intermolecular force ; Materials science ; Hexagonal boron nitride ; Molecule ; Pulmonary surfactant ; Nanotechnology ; Context (archaeology) ; Molecular dynamics ; Hydrogen bond ; Graphene ; Chemical engineering ; Chemistry ; Computational chemistry ; Organic chemistry Graphene research and applications ; Nanopore and Nanochannel Transport Studies ; Luminescence and Fluorescent Materials