jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Semra Çi̇çek
Source: Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi (article, 2022-08-30)
Field: Materials Science — Materials Chemistry

Gökkuşağı alabalığı gonad hücre hattı-2 (RTG-2) üzerinde Eruca vesicaria'dan elde edilen gümüş nanoparçacıkların sitotoksisitesi Gümüş (Ag) nanoparçacıklarının gıda, ilaç, tarım gibi birçok sektörde artan kullanımı ekolojik çevre üzerinde toksik etkilere yol açmaktadır. Bu nedenle Ag nanoparçacık sentez yöntemlerinin neden olduğu toksisiteyi azaltmak için biyolojik sentez yöntemleri üzerinde çalışmalar yapılmaktadır. Bununla birlikte, balık hücre hatlarında biyosentezlenmiş Ag nanoparçacıklarının toksisitesi üzerine yapılan çalışmalar çok azdır. Bu çalışmanın amacı, Eruca vesicaria bitki özü ile Ag nanoparçacıklarının biyolojik sentezini gerçekleştirmek ve gökkuşağı alabalığı gonad hücre hattı-2'de (RTG 2) toksisitelerini incelemektir. E. vesicaria'dan elde edilen Ag nanoparçacıklarının karakterizasyonu UV-vis, TEM ve XRD ile yapılmıştır. Ag nanoparçacıklarının (100 µg/mL- 6,25 µg/mL) 24 saat boyunca RTG-2 hücresindeki toksisitesi sülforodamin B tahlili ile belirlendi. Küre, üçgen, küp ve 5-20 nm boyutlarında elde edilen Ag nanopartiküller, p≤0,001 seviyelerinde doza bağlı olarak RTG-2 balık hücreleri üzerinde önemli toksik etki göstermiştir. Bu çalışma, biyolojik sentez yoluyla elde edilen Ag nanoparçacıklarının balık hücre hatları üzerinde toksik etkisinin olduğunun kanıtlanması ve sentez yöntemlerinden ziyade Ag nanoparçacıklarının çevreye salınımını azaltacak çalışmalara ihtiyaç olduğunu göstermesi açısından önemlidir. Chemistry ; Molecular biology ; Biology Nanoparticles: synthesis and applications ; Advanced Nanomaterials in Catalysis ; Graphene and Nanomaterials Applications
Authors: Thomas F. Schranghamer | Saptarshi Das
Source: Research Square (preprint, 2022-12-14)
Field: Materials Science — Materials Chemistry

Ultra-scaled Phototransistors based on Monolayer MoS2 <title>Abstract</title> For decades, the fundamental diffraction limit of light has stymied the dimension scaling for optoelectronic devices, which remain largely stuck at the micrometer scale or larger. However, recent studies have shown that nanoantennas and plasmonic devices capable of capturing/directing electromagnetic waves are one avenue of artificially focusing incident light into sub-wavelength active areas, thus enabling applications such as photodetection and communication in defiance of the diffraction limit. Despite these advancements, the ultimate scaling limits of photodetector active areas have remained largely untested. In this work, we present a two-dimensional (2D) monolayer molybdenum disulfide (MoS2) photodetector that is able to reach responsivities and detectivities in excess of 108 A/W and 1012 Jones, respectively, and display a high dynamic range while possessing an active area of only 0.0065 μm2. Together, the nano-scale active area and ultra-thin-body nature of the sensing material correspond to an active volume of ~4.23 × 10-6 μm3, approximately 3× smaller than the current smallest photodetector reported in the literature. These results indicate that continued scaling of photodetectors beyond the diffraction limit has enormous potential so long as methods of focusing incident light continued to be developed concurrently. Photodetection ; Photodetector ; Optoelectronics ; Monolayer ; Molybdenum disulfide ; Diffraction ; Materials science ; Wavelength ; Plasmon ; Optics ; Scaling ; Ray ; Active layer ; Physics ; Nanotechnology ; Layer (electronics) 2D Materials and Applications ; Plasmonic and Surface Plasmon Research ; Neural Networks and Reservoir Computing
Authors: Chieh‐Min Hsieh | Björn Grabbet | Felix Zeller | Sanna Benter | Tarek Scheele | Norman Sieroka | Tim Stauch
Source: ChemRxiv (preprint, 2022-06-09)
Field: Chemistry — Physical and Theoretical Chemistry

Can a Finite Chain of Hydrogen Cyanide Molecules Model a Crystal? When calculating structural or spectroscopic properties of molecular crystals, the question arises whether it is sufficient to simulate only a single molecule or a small molecular cluster or whether the simulation of the entire crystal is indispensable. In this work we juxtapose calculations on the high-pressure structural properties of the (periodic) HCN crystal and chains of HCN molecules of finite length. We find that, in most cases, the behavior of the crystal can be reproduced by computational methods simulating only around 15 molecules. The pressure-induced lengthening of the C-H bond in HCN found in calculations on both the periodic and finite material are explained in terms of orbital interaction. Our results pave the way for a more thorough understanding of high-pressure structural properties of materials and give incentives for the design of materials that expand under pressure. In addition, they shed light on the complementarity between calculations on periodic materials and systems of finite size. Molecule ; Hydrogen bond ; Crystal (programming language) ; Crystal structure ; Complementarity (molecular biology) ; Chemical physics ; Work (physics) ; Materials science ; Chemistry ; Crystallography ; Computational chemistry ; Molecular physics ; Physics ; Thermodynamics ; Computer science ; Organic chemistry Crystallography and molecular interactions ; Organic and Molecular Conductors Research ; Inorganic Fluorides and Related Compounds
Authors: Loukas Kollias | Roger Rousseau | Vassiliki‐Alexandra Glezakou | Matteo Salvalaglio
Source: ChemRxiv (preprint, 2022-03-07)
Field: Chemistry — Inorganic Chemistry

Understanding MOF nucleation from solution with Evolving Graphs Metal-Organic Frameworks (MOFs) exhibit attractive characteristics for separations such as remarkable surface area and diverse porosities. However, a mechanistic understanding of their synthesis and scale-up remains underexplored due to the complicated nature of building block interactions. In this work, we investigate the collective assembly of building units that have been experimentally observed to initiate MOF nucleation, using MIL-101(Cr) as a prototypical example. We use large-scale molecular dynamics simulations under a variety of synthesis conditions and mixture compositions. We observe that the choice of solvent (water or DMF), introduction of ions (Na+, F-) and the relative population of MIL-101(Cr) half-secondary building unit (half-SBU) isomers has a strong influence on the cluster formation process. In more detail, the shape, size, nucleation and growth rates, crystallinity and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting self-assembly of MOF nuclei as the time-evolution of an undirected graph. Solution-induced con-formational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly, such diversity is captured by key features of the graph representation. More precisely, pure solvent leads to rapid formation of a small number of large clusters, while ions result in slower nucleation through smaller clusters in water. Finally, we use Principal Component Analysis (PCA) on graph properties to successfully deconvolute MOF self-assembly into a small number of molecular descriptors, such as the average coordination number between half-SBUs and fractal dimension, which can be followed by time-resolved spectroscopy. We conclude that graph theory can be used to understand complex processes such as MOF nucleation through providing molecular descriptors accessible by both simulation and experiment. Nucleation ; Crystallinity ; Chemical physics ; Ionic bonding ; Ionic liquid ; Cluster (spacecraft) ; Materials science ; Ion ; Molecular dynamics ; Chemistry ; Computational chemistry ; Computer science ; Crystallography ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; X-ray Diffraction in Crystallography ; Machine Learning in Materials Science
Authors: Anitha Nilavan | Nellainayagam Narendran | Veerapandian Velkannan | Shree Nithiya | Gurmeet Singh | Hashem Abdulhameed Al | S. Rajendran | Časlav Lačnjevac
Source: Zastita materijala (article, 2022-12-15)
Field: Materials Science — Materials Chemistry

Corrosion resistance of orthodontic wire made of nickel-titanium alloy in artificial saliva in the presence of Kopiko candy Corrosion resistance of an orthodontic wire made of Ni-Ti alloy immersed in artificial saliva in the absence and presence of 500 ppm of Kopiko candy has been investigated by polarization study and AC impedance spectra. It is observed that corrosion resistance of Ni-Ti alloy immersed in artificial saliva in the presence of 500 ppm of Kopiko candy increases. Hence it is concluded that people clipped with orthodontic wire made of Ni-Ti alloy need not worry about taking Kopiko candy orally. When Ni-Ti alloy is immersed in artificial saliva in the presence of 500 ppm of Kopiko candy, Linear Polarization Resistance value increases from 347978 Ohmcm2 to 415003 Ohmcm2 ; corrosion current decreases from 1.346 x10-7A/cm2 to 1.105 x10-7A/cm2 ; charge transfer resistance value increases from 31945 Ohmcm2 to 44357 Ohmcm2 ; impedance value increases from 4.649to 4.819; double layer capacitance decreases from 1.596x10-10F/cm2 to 1.150 x10-10F/cm2 , and phase angle increases from 39.63° to 50°. Materials science ; Corrosion ; Alloy ; Saliva ; Capacitance ; Metallurgy ; Double-layer capacitance ; Polarization (electrochemistry) ; Composite material ; Electrical impedance ; Dielectric spectroscopy ; Chemistry ; Electrode ; Electrical engineering ; Electrochemistry Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Welding Techniques and Residual Stresses
Authors: Gunnar Alexander Schmitz | Bastian Schnieder
Source: Journal of Computational Chemistry (article, 2022-11-16)
Field: Materials Science — Materials Chemistry

Adaptive regularized Gaussian process regression for application in the context of hydrogen adsorption on graphene sheets We present a Gaussian process regression (GPR) scheme with an adaptive regularization scheme applied to the QM7 and QM9 test set, several protonated water clusters and specifically to the problem of atomic hydrogen adsorption on graphene sheets. For the last system our goal is to achieve good predictive accuracy with only a few training points. Therefore, we assess for these systems a self-correcting multilayer GPR model, in which the prediction is corrected by a chain of additional GPR models. In our adaptive regularization scheme, we impose no noise on the training data, but use an approach based on the data itself to account for its impurity. The strength of this strategy is that the data points are treated differently based on their importance and that the regularization can still be controlled by a single parameter. We assess how the accuracy of the prediction depends on this parameter. We can show that the new regularization scheme as well as the multilayer approach results in more robust predictors. Furthermore, we demonstrate that the predictor can be in good agreement with the density-functional theory results. Regularization (linguistics) ; Computer science ; Gaussian process ; Gaussian ; Regression ; Algorithm ; Mathematical optimization ; Applied mathematics ; Mathematics ; Artificial intelligence ; Chemistry ; Statistics ; Computational chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: Alan Bilsland | Angelo Pugliese | Justin Bower
Source: RSC Medicinal Chemistry (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Implementation of an AI-assisted fragment-generator in an open-source platform We recently reported a deep learning model to facilitate fragment library design, which is critical for efficient hit identification. However, our model was implemented in Python. We have now created an implementation in the KNIME graphical pipelining environment which we hope will allow experimentation by users with limited programming knowledge. Fragment (logic) ; Workflow ; Computer science ; Open source ; Generator (circuit theory) ; Identification (biology) ; Software engineering ; Operating system ; Programming language ; Computer architecture ; Software ; Database Machine Learning in Materials Science ; Topic Modeling ; Scientific Computing and Data Management
Authors: Parashiva Murthy Srinivas | Jade Madegowda Mahadeva | K. Hemalatha | M B Nandaprakash | R. Somashekar
Source: European Journal of Applied Physics (article, 2022-12-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Thermodynamic Morphological Study of Liquid Crystalline Compounds Thermodynamic morphism study has been envisaged using search procedure of phase space of polymorphs at a prescribed temperature and pressure(NPT) of several azoxybenzenes based liquid crystalline compounds at room temperature using molecular structure, unit cell information and AMOEBA parameters employing Force Field computation (FFX) calculations. These calculations were carried out at various intermolecular strengths to understand the morphological walk of molecules with corresponding changes in free energy, change in a force field with a strength of the interactions and free energy difference between successive interaction strengths. This study will help us to understand the nature, range and type of mesophase in a series of azoxybenzene compounds. Intermolecular force ; Mesophase ; Molecule ; Force field (fiction) ; Thermodynamics ; Materials science ; Liquid crystal ; Chemical physics ; Chemistry ; Computational chemistry ; Organic chemistry ; Physics Liquid Crystal Research Advancements ; Chemical Thermodynamics and Molecular Structure ; Crystallization and Solubility Studies
Authors: Niklas H. Fischer | Sara Lopes van den Broek | Matthias M. Herth | Frederik Diness
Source: RSC Advances (article, 2022-01-01)
Field: Chemistry — Organic Chemistry

Radiolabeled albumin through S<sub>N</sub>Ar of cysteines as a potential pretargeting theranostic agent Human serum albumin (HSA) has been shown to be a promising tumor targeting vector and target for generating theranostics by bioconjugation. Unstable chemical conjugation to HSA <i>via</i> a cysteine (Cys34) by reversible Michael additions is most commonly applied for this purpose. Herein, we describe utilization of our recently developed site-selective irreversible S<sub>N</sub>Ar conjugation to Cys34 using perfluorobenzene sulfonyl derivatives to introduce a <i>trans</i>-cyclooctene (TCO) handle. The TCO could then be bioorthogonally ligated within minutes through an inverse-electron demand Diels-Alder reaction (IEDDA) to tetrazines (Tzs) containing a radionuclide. The methodology opens up a wide range of chemistries including pretargeting, 'click-to-release' tumor selective drug delivery or ultra-fast and complete conjugation of any drug. The proof-of-principle study demonstrated that the conjugation chemistry is feasible, robust and easy to carry out, being promising for pretargeted imaging and therapy studies as well as selective drug delivery using HSA. Pretargeting ; Bioorthogonal chemistry ; Chemistry ; Bioconjugation ; Combinatorial chemistry ; Human serum albumin ; Drug delivery ; Conjugate ; Conjugated system ; Click chemistry ; Organic chemistry ; Biochemistry ; Radioimmunotherapy Click Chemistry and Applications ; Monoclonal and Polyclonal Antibodies Research ; Chemical Synthesis and Analysis
Authors: Sabyasachi Roy Chowdhury | Ngan Nguyen | Bess Vlaisavljevich
Source: ChemRxiv (preprint, 2022-11-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Importance of Dispersion in the MolecularGeometries of Mn(III) Spin Crossover Complexes We report the computational investigation of the molecular geometries of a pair of manganese(III) spin crossover complexes. For the high-spin geometry, the density functionals significantly overestimate the Mn−Namine bond distances, although the geometry for the intermediate-spin is well-described. Comparisons with several wavefunction-based methods demonstrate that this error is due to the limited ability of density functional theory (DFT) to recover dispersion beyond a certain extent. Among the methods employed for geometry optimization, Møller-Plesset perturbation theory (MP2) appropriately describes the high-spin geometry, but results in a slightly reduced Mn−O distance in both the spin-states. On the other hand, complete active space second-order perturbation theory (CASPT2) results in a good description of the geometry for the intermediate spin state, but also sufficiently recovers dispersion performing well for the high-spin state. Despite the fact that the electronic structure of both spin states is dominated by one electron configuration, CASPT2 offers a balanced approach leading to molecular geometries with much better accuracy than MP2 and DFT. A scan along the Mn−Namine bond demonstrates that coupled cluster methods (i.e., DLPNO-CCSD(T)) also yield bond distances in agreement with experiment, while multiconfiguration pair density functional theory (MC-PDFT) is unable to recover dispersion well enough, analogous to single reference DFT. Density functional theory ; Perturbation theory (quantum mechanics) ; Bond length ; Coupled cluster ; Wave function ; Spin (aerodynamics) ; Spin states ; Molecular geometry ; Physics ; Geometry ; Chemistry ; Molecular physics ; Molecule ; Atomic physics ; Quantum mechanics ; Mathematics ; Thermodynamics Magnetism in coordination complexes ; Metal-Catalyzed Oxygenation Mechanisms ; Metal complexes synthesis and properties
Authors: Alastair J. A. Price | Alberto Otero‐de‐la‐Roza | Erin R. Johnson
Source: ChemRxiv (preprint, 2022-10-20)
Field: Chemistry — Physical and Theoretical Chemistry

XDM-Corrected Hybrid DFT with Numerical Atomic Orbitals Predicts Molecular Crystal Lattice Energies with Unprecedented Accuracy Molecular crystals are important for many applications, including energetic materials, organic semiconductors, and the development and commercialization of pharmaceuticals. Molecular crystal structure prediction (CSP) relies on the use of accurate and inexpensive computational methods to rank candidate crystal structures. The exchange-hole dipole moment (XDM) model has shown excellent performance in the calculation of relative and absolute lattice energies of molecular crystals in the past. XDM has traditionally been applied in combination with plane-wave/pseudopotential approaches and therefore limited to semilocal functional approximations, which suffer from delocalization error and poor quality conformational energies, and to systems with a few hundreds of atoms at most due to unfavorable scaling. In this work, we combine XDM with numerical atomic orbitals (NAO), which enable the use of XDM-corrected hybrid functionals for molecular crystals, mitigating these three problems. We test the XDM-corrected functionals for their ability to predict the lattice energies of molecular crystals in the X23 set and of 13 ice phases, the latter being a particularly stringent test. It is shown that a composite XDM-corrected hybrid functional based on B86bPBE-XDM achieves an average error of 0.48 kcal/mol per molecule in the X23 set and 0.19 kcal/mol in the absolute lattice energies of the ice phases compared to recent diffusion Monte Carlo data. These results make the new XDM-corrected hybrids not only far more computationally efficient than previous XDM implementations, but also the most accurate density-functional methods for molecular crystal lattice energies to date. Pseudopotential ; Hybrid functional ; Crystal structure prediction ; Density functional theory ; Lattice energy ; Crystal (programming language) ; Delocalized electron ; Dipole ; Molecular orbital ; Lattice (music) ; Atomic orbital ; Crystal structure ; Physics ; Statistical physics ; Molecular physics ; Materials science ; Chemistry ; Computational chemistry ; Atomic physics ; Molecule ; Quantum mechanics ; Crystallography ; Computer science Crystallography and molecular interactions ; Advanced Chemical Physics Studies ; Solid-state spectroscopy and crystallography
Authors: Abu Shaid Sujon | Jeppe Madsen | Jesper de Claville Christiansen | Aminul Islam
Source: Journal of Applied Polymer Science (article, 2022-11-05)
Field: Materials Science — Polymers and Plastics

Enhancement of viscoelastic property of <scp>MABS</scp> processed by melt compounding and injection molding Abstract This work is focused on developing a new type of polymer blend to improve the viscoelastic property of methyl methacrylate acrylonitrile butadiene styrene (MABS). A multi‐phase binary polymer blend was prepared by melt mixing in a twin screw extruder with three different weight ratios (10, 20, and 30 wt%) with a dynamically vulcanized alloy consisting mostly of fully cured ethylene propylene diene rubber (EPDM) particles encapsulated in a polypropylene (PP) matrix trade name Santoprene and an engineered styrene based thermoplastic elastomer trade name VDT to enhance the viscoelastic property of the blends. The compatibility and performance of the binary blend were studied by differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), Fourier transform infrared (FT‐IR) spectroscopy, nuclear magnetic resonance (NMR), laser microscopy, scanning transmission electron microscopy (STEM) and tensile analysis. The DMA analysis of the samples revealed that the damping performance was significantly increased with the incorporation of the elastomeric phase into the MABS matrix. In addition, the morphological analysis revealed that VDT is more compatible with MABS compared to Santoprene. The NMR and FT‐IR analysis further supported the reason for higher compatibility of VDT and MABS blend. The improvement of the damping properties has been observed with the increased wt % of the VDT and Santoprene in the blends. Materials science ; Dynamic mechanical analysis ; Composite material ; Differential scanning calorimetry ; Elastomer ; Polymer blend ; Compatibilization ; Polymer ; Vulcanization ; Fourier transform infrared spectroscopy ; Miscibility ; Curing (chemistry) ; Natural rubber ; Chemical engineering ; Copolymer Polymer Nanocomposites and Properties ; Polymer crystallization and properties ; Polymer composites and self-healing