jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shanju Zhang | Uwe H. F. Bunz | David G. Bucknall
Source: Journal of Composites Science (article, 2021-06-14)
Field: Materials Science — Polymers and Plastics

Chromatic Conductive Polymer Nanocomposites of Poly (p-Phenylene Ethynylene)s and Single-Walled Carbon Nanotubes We report on dispersions and thin films of chromatic conductive nanocomposites of poly(p-phenylene ethynylene)s (PPEs) and single-walled carbon nanotubes (SWNTs) generated via solution mixing. The linear, conjugated PPEs with dialkyl- and dialkyloxy-side chain groups are shown to debundle and disperse high concentration (up to 2.5 mg/mL) SWNTs in various organic solvents. The solubilization of SWNTs and PPE wrapping is accompanied with the change in the solution color. Ultraviolet visible absorption spectra of nanocomposite solutions demonstrate a new absorption peak at a higher wavelength, supporting the observed chromatism. Fluorescence spectra of nanocomposite solutions display significant quenching of the fluorescence intensity and the Stern–Volmer model is used to analyze fluorescence quenching. Electron microscopy of the chromatic solid films of high mass fraction PPE/SWNT nanocomposites obtained by vacuum filtration reveals the debundled SWNTs in the PPE matrix. The tensile strength and Young’s modulus of these PPE/SWNT nanocomposite films are as high as 150 MPa and 15 GPa, respectively. The composite films exhibit remarkably high conductivities, ranging from ~1000 S/m to ~10,000 S/m for 10 wt% and 60 wt% SWNT nanocomposites, respectively. Nanocomposite ; Materials science ; Carbon nanotube ; Polymer ; Phenylene ; Quenching (fluorescence) ; Composite material ; Absorption (acoustics) ; Composite number ; Chemical engineering ; Polymer chemistry ; Fluorescence ; Optics Conducting polymers and applications ; Organic Electronics and Photovoltaics ; Carbon Nanotubes in Composites
Authors: Uzma Haseen | Syed Ghazanfar Ali | Khalid Umar | Abuzer Ali | Hilal Ahmad | Haris M. Khan
Source: Water (article, 2021-11-01)
Field: Chemistry — Analytical Chemistry

Dimercaptosuccinic Acid Functionalized Polystyrene Column for Trace Concentration Determination of Heavy Metal Ions: Experimental and Theoretical Calculation Studies Metal ion studies in wastewater are required on a regular basis for environmental monitoring and assessment. Less metal ion concentrations and the interference from complex sample matrices remains challenging for instrumental quantification. Herein, we proposed a fix-bed solid phase extraction method, consisting of a newly prepared dimercaptosuccinic acid functionalized polystyrene beads. The ligand forms stable complex with Hg(II), Pb(II), and Cd(II), evident by experimental as well as density functional theory. The metal-ligand stabilization energy calculations, suggested the higher selectivity of polystyrene dimercaptosuccinic acid (PSDMSA) toward Pb(II) compared to Cd(II) and Hg(II). The prepared adsorbent was utilized to enrich Hg(II), Pb(II), and Cd(II) ions from environmental samples. Column parameters were studied in detail and optimized accordingly. The preconcentration factor for Hg(II), Pb(II), and Cd(II) were found to be 900, with the preconcentration limit of 0.74 µg L−1. The detection limit for Pb(II), Cd(II), and Hg(II) ions was found to be 1.3 ± 0.2, 1.5 ± 0.3, and 1.8 ± 0.3 ng L−1, respectively. The method accuracy was tested against systematic and continuous errors by standard addition method (&lt;5% RSD). Real samples was successfully analyzed following the proposed method. Detection limit ; Metal ions in aqueous solution ; Chemistry ; Polystyrene ; Metal ; Solid phase extraction ; Adsorption ; Extraction (chemistry) ; Ligand (biochemistry) ; Trace Amounts ; Nuclear chemistry ; Analytical Chemistry (journal) ; Chromatography ; Polymer ; Physical chemistry Analytical chemistry methods development ; Radioactive element chemistry and processing ; Electrochemical Analysis and Applications
Authors: Saswata Dasgupta | Eleftherios Lambros | John P. Perdew | Francesco Paesani
Source:  (preprint, 2021-10-05)
Field: Materials Science — Materials Chemistry

Elevating Density Functional Theory to Chemical Accuracy for Water Simulations through a Density-Corrected Many-Body Formalism Density functional theory (DFT) has been extensively used to model the properties of water. Albeit maintaining a good balance between accuracy and efficiency, no density functional has so far achieved the degree of accuracy necessary to correctly predict the properties of water across the entire phase diagram. Here, we present density-corrected SCAN (DC-SCAN) calculations for water which, minimizing density-driven errors, elevate the accuracy of the SCAN functional to that of “gold standard” coupled-cluster theory. Building upon the accuracy of DC-SCAN within a many-body formalism, we introduce a data-driven many-body potential energy function, MB-SCAN(DC), that quantitatively reproduces coupled cluster reference values for interaction, binding, and individual many-body energies of water clusters. Importantly, molecular dynamics simulations carried out with MB-SCAN(DC) also reproduce the properties of liquid water, which thus demonstrates that MB-SCAN(DC) is effectively the first DFT-based model that correctly describes water from the gas to the liquid phase. Formalism (music) ; Density functional theory ; Phase diagram ; Water body ; Liquid water ; Statistical physics ; Cluster (spacecraft) ; Physics ; Computational physics ; Phase (matter) ; Computer science ; Thermodynamics ; Quantum mechanics ; Environmental science Machine Learning in Materials Science ; Theoretical and Computational Physics ; Spectroscopy and Quantum Chemical Studies
Authors: Amin Alibakhshi
Source: ChemRxiv (preprint, 2021-09-27)
Field: Chemistry — Organic Chemistry

High precision evaluation of the combustion enthalpy byab-intio computations Accurate evaluation of combustion enthalpy is of high scientific and industrial importance. Although via ab-initio computation of heat of reactions, as one of the promising and well-established approaches in computational chemistry, this goal should in principle be achievable, examples of reliable and precise evaluation of heat of combustion by ab-initio methods has surprisingly not yet been reported. A handful of works carried out for this purpose report significant inconsistencies between the ab-initio evaluated and experimentally determined combustion enthalpies and suggest empirical corrections to improve the accuracy of predicted data. With this background, the main aims of the present study is to investigate the reasons behind those reported inconsistencies and propose guidelines for highly accurate evaluation of combustion enthalpy via ab-initio computations. Through the provided guidelines, the most accurate results ever reported, with average absolute deviation, mean unsigned error and correlation coefficient of 1.556 kJ/mole, 0.072% and 0.99999, respectively, is achieved for theoretically computed combustion enthalpies of 40 studied hydrocarbons. Combustion ; Ab initio ; Computation ; Enthalpy ; Thermodynamics ; Standard enthalpy of formation ; Ab initio quantum chemistry methods ; Absolute deviation ; Chemistry ; Standard enthalpy change of formation ; Computational chemistry ; Physical chemistry ; Computer science ; Mathematics ; Algorithm ; Physics ; Statistics ; Molecule ; Organic chemistry Chemical Thermodynamics and Molecular Structure ; Phase Equilibria and Thermodynamics ; thermodynamics and calorimetric analyses
Authors: Eva I. Hyde | Alex Ka-Wing Chau | Lorna J. Smith
Source: Biomolecular NMR Assignments (article, 2021-01-09)
Field: Materials Science — Materials Chemistry

Backbone assignment of E. coli NfsB and the effects of addition of the cofactor analogue nicotinic acid E. coli nitroreductase NfsB (also called NfnB) has been studied extensively, largely due to its potential for cancer gene therapy. A homodimeric flavoprotein of 216 residues, it catalyses the reduction of nitroaromatics to cytotoxic hydroxylamines by NADH and NADPH and also the reduction of quinones to hydroxyquinones. Its role in vivo is not known but it is postulated to be involved in reducing oxidative stress. The crystal structures of the wild type protein and several homologues have been determined in the absence and presence of ligands, including nicotinate as a mimic of the headpiece of the nicotinamide cofactors. There is little effect on the overall structure of the protein on binding ligands, but, from the B factors, there appears to be a decrease in mobility of 2 helices near the active site. As a first step towards examining the dynamics of the protein in solution with and without ligand, we have assigned the backbone <sup>13</sup>C, <sup>15</sup>N, and <sup>1</sup>H<sub>N</sub> resonances of NfsB and examined the effect of the binding of nicotinate on the amide <sup>15</sup>N, and <sup>1</sup>H<sub>N</sub> shifts. Cofactor ; Nicotinic agonist ; Chemistry ; Biochemistry ; Enzyme Enzyme Structure and Function ; RNA and protein synthesis mechanisms ; Microbial Metabolic Engineering and Bioproduction
Authors: Mariam Tangarfa | Naoual Semlali Aouragh Hassani
Source: Physicochemical Problems of Mineral Processing (article, 2021-11-27)
Field: Materials Science — Biomaterials

The behaviour of tannic acid adsorption on fluorite surface: Isotherm, kinetic and thermodynamic studies Fluorite is an important mineral to produce hydrofluoric acid. As fluorite resources contain calcite as a gangue mineral, the separation between these two calcium containing minerals is difficult. Tannic acid is the most commonly used reagent as a depressant to separate fluorite from calcite by flotation. To enhance this separation, it is so primordial to understand tannic acid physicochemical reactivity via these minerals. Therefore, the aim of this work is to investigate the mechanism of tannic acid adsorption on the fluorite surface by experimental study using isotherm, kinetic and thermodynamic. Adsorption isotherm modelling results showed that the adsorption process is well described by Sips model. On the other hand, the kinetic and thermodynamic require firstly the adsorption study as a function of three main reactional parameters including initial tannic acid concentration, solution pH and temperature. This study showed that acidic pH as well as initial tannic acid concentration increase and temperature decrease promote the studied adsorption. These finding were then exploited to determine the adsorption mechanism by pseudo n order kinetic model adjustment to experimental kinetic data using nonlinear regression method. Obtained high correlation coefficient and low mean absolute error at 95 % confidence level showed good agreement of experimental kinetic data with the tested model. These results revealed that the mechanism of tannic acid adsorption onto fluorite was attributed to a chemical reaction. In addition, the thermodynamic study showed that the studied adsorption process was exothermic. Tannic acid ; Adsorption ; Fluorite ; Chemistry ; Kinetic energy ; Chemical engineering ; Physical chemistry ; Organic chemistry Calcium Carbonate Crystallization and Inhibition ; Minerals Flotation and Separation Techniques ; Methane Hydrates and Related Phenomena
Authors: Hannah Melia | Eric S. Muckley | James E. Saal
Source: Data-Centric Engineering (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Materials informatics and sustainability—The case for urgency Abstract The development of transformative technologies for mitigating our global environmental and technological challenges will require significant innovation in the design, development, and manufacturing of advanced materials and chemicals. To achieve this innovation faster than what is possible by traditional human intuition-guided scientific methods, we must transition to a materials informatics-centered paradigm, in which synergies between data science, materials science, and artificial intelligence are leveraged to enable transformative, data-driven discoveries faster than ever before through the use of predictive models and digital twins. While materials informatics is experiencing rapidly increasing use across the materials and chemicals industries, broad adoption is hindered by barriers such as skill gaps, cultural resistance, and data sparsity. We discuss the importance of materials informatics for accelerating technological innovation, describe current barriers and examples of good practices, and offer suggestions for how researchers, funding agencies, and educational institutions can help accelerate the adoption of urgently needed informatics-based toolsets for science in the 21st century. Transformative learning ; Informatics ; Sustainability ; Materials informatics ; Engineering ethics ; Knowledge management ; Engineering informatics ; Data science ; Computer science ; Management science ; Engineering ; Political science ; Health informatics ; Sociology Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: Siddhartha Kundu
Source: BMC Research Notes (article, 2021-03-01)
Field: Chemistry — Inorganic Chemistry

Fe(2)OG: an integrated HMM profile-based web server to predict and analyze putative non-haem iron(II)- and 2-oxoglutarate-dependent dioxygenase function in protein sequences This work reports the implementation of [Formula: see text], a web server with dual functionality and an extension of previous work on i2OGdd enzymes [Formula: see text]. [Formula: see text], in this form is completely revised, updated (URL, scripts, repository) and will strengthen the knowledge base of investigators on i2OGdd biochemistry and function. [Formula: see text], utilizes the superior predictive propensity of HMM-profiles of laboratory validated i2OGdd members to predict probable active site geometries in user-defined protein sequences. [Formula: see text], also provides researchers with a pre-compiled list of analyzed and searchable i2OGdd-like sequences, many of which may be clinically relevant. [Formula: see text], is freely available ( http://204.152.217.16/Fe2OG.html ) and supersedes all previous versions, i.e., H2OGpred, DB2OG. Algorithm ; Computer science ; Chemistry Metal-Catalyzed Oxygenation Mechanisms ; Enzyme Catalysis and Immobilization ; Microbial Metabolic Engineering and Bioproduction
Authors: Zhiyuan Hu
Source: PLoS ONE (article, 2021-08-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Fe-based superconducting transition temperature modeling by machine learning: A computer science method Searching for new high temperature superconductors has long been a key research issue. Fe-based superconductors attract researchers' attention due to their high transition temperature, strong irreversibility field, and excellent crystallographic symmetry. By using doping methods and dopant levels, different types of new Fe-based superconductors are synthesized. The transition temperature is a key indicator to measure whether new superconductors are high temperature superconductors. However, the condition for measuring transition temperature are strict, and the measurement process is dangerous. There is a strong relationship between the lattice parameters and the transition temperature of Fe-based superconductors. To avoid the difficulties in measuring transition temperature, in this paper, we adopt a machine learning method to build a model based on the lattice parameters to predict the transition temperature of Fe-based superconductors. The model results are in accordance with available transition temperatures, showing 91.181% accuracy. Therefore, we can use the proposed model to predict unknown transition temperatures of Fe-based superconductors. Superconductivity ; Condensed matter physics ; Transition temperature ; Superconducting transition temperature ; High-temperature superconductivity ; Dopant ; Doping ; Materials science ; Lattice (music) ; Physics ; Engineering physics Iron-based superconductors research ; Rare-earth and actinide compounds ; Physics of Superconductivity and Magnetism
Authors: Muhammad Zohaib Fazal | Sharifullah Khan | Muhammad Azeem Abbas | Yasir Nawab | Muhammad Shahzad Younis
Source: Tehnicki vjesnik - Technical Gazette (article, 2021-02-07)
Field: Materials Science — Polymers and Plastics

Machine Learning Approach for Prediction of Crimp in Cotton Woven Fabrics The interlacements of yarns in woven fabrics cause the yarn to follow a wavy path that produces crimp. Off-loom width of the fabric is determined by the percentage of the induced crimp. Therefore, the final width of the fabric will be less or surplus than required if crimp percentage is not precisely measured. Both excessive or recessive fabric width is unwanted and leads to huge loss of cost (profit), manufacturing time, energy (electricity) and ultimately loss of competition. Crimp percentage in yarns is determined by physically measuring the extra yarn length or by predicting it based on fabric structural parameters. Existing methods are mainly post-production, time and resource intensive that require specialized skills and tangible fabric samples. The proposed framework applies supervised machine learning for crimp prediction to cater for the limitations of the existing techniques. The framework has been cross-validated and has prediction accuracy (R 2 ) of 0.86 and 0.79 for warp and weft yarn crimp respectively. It has prediction accuracy (R 2 ) for warp and weft yarns crimp of 0.99 and 0.81 respectively for the unseen industrial dataset. The proposed prediction model shows better performance when compared with an existing standard system. 8p Crimp ; Woven fabric ; Composite material ; Materials science ; Machine learning ; Artificial intelligence ; Polymer science ; Computer science Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Material Properties and Processing
Authors: Beket Kenzhegulov | Raigul Tuleuova | Aigul Myrzasheva | Nurgul Shazhdekeyeva | Galymzhan Kabylkhamitov
Source: Periodicals of Engineering and Natural Sciences (PEN) (article, 2021-09-15)
Field: Materials Science — Materials Chemistry

Mathematical modelling and development of a computational algorithm for the study of thermo-stressed state of a heat-resistant alloy The problem of increasing the thermal stability of structural elements made of heat-resistant metals and alloys operating in a complex force and thermal field is one of the key priorities of modern high technology research. The most important case is the study of the thermal stability of structural elements in real conditions of heat fluxes with varying intensity, with a complex configuration of heat-insulated local surfaces and internal point heat sources. Many basic load-bearing structural elements operating in a large thermal field (elements of gas turbine and jet engines, etc.), are made of heat-resistant alloys. The physical feature of such alloys is that the coefficient of thermal expansion and the modulus of elasticity of the material strictly depends on the temperature distribution field, that is, the coefficients are a function of temperature. The purpose of this study is to simulate a thermo-stressed state in rod elements of a structure based on the law of conservation of energy, in the presence of a heat flux applied on the lateral surface, which varies along the coordinate in a linear manner. To solve the outlined problem, a potential energy minimisation method is used in combination of a quadratic finite element with three nodes. As a result, from the condition of the minimum of the functional defining the potential energy, a resolving system of linear algebraic equations is obtained. All possible natural boundary conditions are taken into account. In this system, all integrals used are calculated analytically. Moreover, the law of conservation of energy is fulfilled for each of the equations of the resulting system. As a result, the values of displacement, deformation and stresses were calculated, as well as the values of elastic temperature and thermoelastic components of deformations and stresses for a specific example. Boundary value problem ; Finite element method ; Thermal ; Conservation of energy ; Energy conservation ; Heat transfer ; Mechanics ; Mechanical engineering ; Thermodynamics ; Materials science ; Mathematics ; Physics ; Engineering ; Mathematical analysis Structural mechanics and materials ; Heat Transfer and Mathematical Modeling ; Material Properties and Applications
Authors: Alastair D. G. Lawson | Malcolm MacCoss | Dominique Baeten | Alex Macpherson | Jiye Shi | Alistair J. Henry
Source: Frontiers in Chemistry (article, 2021-05-04)
Field: Chemistry — Organic Chemistry

Modulating Target Protein Biology Through the Re-mapping of Conformational Distributions Using Small Molecules Over the last 10 years considerable progress has been made in the application of small molecules to modulating protein-protein interactions (PPIs), and the navigation from "undruggable" to a host of candidate molecules in clinical trials has been well-charted in recent, comprehensive reviews. Structure-based design has played an important role in this scientific journey, with three dimensional structures guiding medicinal chemistry efforts. However, the importance of two additional dimensions: movement and time is only now being realised, as increasing computing power, closely aligned with wet lab validation, is applied to the challenge. Protein dynamics are fundamental to biology and disease, and application to PPI drug discovery has massively widened the scope for new chemical entities to influence function from allosteric, and previously unreported, sites. In this forward-looking perspective we highlight exciting, new opportunities for small molecules to modulate disease biology, by adjusting the frequency profile of natural conformational sampling, through the stabilisation of clinically desired conformers of target proteins. Small molecule ; Chemical biology ; Drug discovery ; Allosteric regulation ; Computational biology ; Scope (computer science) ; Chemical space ; Nanotechnology ; Structural biology ; Function (biology) ; Intrinsically disordered proteins ; Data science ; Chemistry ; Computer science ; Biology ; Bioinformatics ; Biophysics ; Materials science ; Biochemistry ; Cell biology Click Chemistry and Applications ; Monoclonal and Polyclonal Antibodies Research ; RNA and protein synthesis mechanisms
Authors: Chuangchuang Duan | Yujie Wei
Source: Science China Materials (article, 2021-11-30)
Field: Materials Science — Materials Chemistry

Grain boundary diffusion and viscous flow governed mechanical relaxation in polycrystalline materials Materials science ; Crystallite ; Grain boundary ; Relaxation (psychology) ; Shearing (physics) ; Internal friction ; Grain boundary diffusion coefficient ; Stress relaxation ; Diffusion ; Condensed matter physics ; Mechanics ; Composite material ; Thermodynamics ; Creep ; Physics ; Metallurgy ; Microstructure Material Dynamics and Properties ; Theoretical and Computational Physics ; Metallic Glasses and Amorphous Alloys