jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ibón Alkorta | Arnaldo F. Silva | Paul L. A. Popelier
Source: Molecules (article, 2020-06-09)
Field: Chemistry — Physical and Theoretical Chemistry

An Interacting Quantum Atoms (IQA) and Relative Energy Gradient (REG) Study of the Halogen Bond with Explicit Analysis of Electron Correlation Energy profiles of seven halogen-bonded complexes were analysed with the topological energy partitioning called Interacting Quantum Atoms (IQA) at MP4(SDQ)/6-31+G(2d,2p) level of theory. Explicit interatomic electron correlation energies are included in the analysis. Four complexes combine X<sub>2</sub> (X = Cl or F) with HCN or NH<sub>3</sub>, while the remaining three combine ClF with HCN, NH<sub>3</sub> or N<sub>2</sub>. Each complex was systematically deformed by translating the constituent molecules along its central axis linking <i>X</i> and <i>N</i>, and reoptimising its remaining geometry. The Relative Energy Gradient (REG) method (<i>Theor. Chem. Acc.</i> <b>2017</b>, <i>136</i>, 86) then computes which IQA energies most correlate with the total energy during the process of complex formation and further compression beyond the respective equilibrium geometries. It turns out that the covalent energy (i.e., exchange) of the halogen bond, X…N, itself drives the complex formation. When the complexes are compressed from their equilibrium to shorter X…N distance then the intra-atomic energy of <i>N</i> is in charge. When the REG analysis is restricted to electron correlation then the interatomic correlation energy between X and N again drives the complex formation, and the complex compression is best described by the destabilisation of the through-space correlation energy between N and the "outer" halogen. Chemistry ; Electronic correlation ; Halogen ; Atomic physics ; Covalent bond ; Energy (signal processing) ; Electron ; Molecule ; Computational chemistry ; Crystallography ; Molecular physics ; Physics ; Quantum mechanics Crystallography and molecular interactions ; Inorganic Fluorides and Related Compounds ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Justyna Godyń | Dominika Gucwa | Tereza Kobrlová | Martin Novák | Ondřej Soukup | Barbara Malawska | Marek Bajda
Source: Talanta (article, 2020-04-11)
Field: Chemistry — Electrochemistry

Novel application of capillary electrophoresis with a liposome coated capillary for prediction of blood-brain barrier permeability Profiling blood-brain barrier permeability of bioactive molecule is an important issue in early drug development, being a part of the optimization process of a compound's physicochemical properties, and hence pharmacokinetic profile. The study aimed to develop and optimize a new in vitro method for assessment of the compound's brain penetration. The tool is proposed as an alternative to the PAMPA-BBB (Parallel Artificial Membrane Permeability Assay for Blood-Brain Barrier) and based on a capillary electrochromatography (CEC) technique. It utilizes liposomes as structural substitutes of biological membranes, which are used as a capillary inner wall coating material. Following optimization of analysis conditions, migration times for a set of 25 reference drugs (mainly non-ionized in pH 7.4) were examined in a liposome coated capillary. On that basis, the retention factor (log k) was determined for each reference drug. Obtained log k values and experimentally received reference permeability parameters: log BB (in vivo data) and log P<sub>e</sub> (PAMPA-BBB data) were compared with one another. Correlation coefficients were calculated, giving comparable results for CEC log k/log BB and analogical PAMPA-BBB log P<sub>e</sub>/log BB analyses. Approximate ranges of log k for the central nervous system (CNS) permeable (CNS(+)) and non-permeable (CNS(-)) drugs were established. Chemistry ; Capillary electrophoresis ; Liposome ; Blood–brain barrier ; Capillary action ; Chromatography ; Permeability (electromagnetism) ; Penetration (warfare) ; Membrane ; Capillary electrochromatography ; Permeation ; Central nervous system ; Biochemistry Electrochemical Analysis and Applications ; Neuroscience and Neuropharmacology Research ; Lipid Membrane Structure and Behavior
Authors: Haiyan Wang | Rafael Piestun
Source: Scientific Reports (article, 2020-04-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Azimuthal multiplexing 3D diffractive optics Diffractive optics have increasingly caught the attention of the scientific community. Classical diffractive optics are 2D diffractive optical elements (DOEs) and computer-generated holograms (CGHs), which modulate optical waves on a solitary transverse plane. However, potential capabilities are missed by the inherent two-dimensional nature of these devices. Previous work has demonstrated that extending the modulation from planar (2D) to volumetric (3D) enables new functionalities, such as generating space-variant functions, multiplexing in the spatial or spectral domain, or enhancing information capacity. Unfortunately, despite significant progress fueled by recent interest in metasurface diffraction, 3D diffractive optics still remains relatively unexplored. Here, we introduce the concept of azimuthal multiplexing. We propose, design, and demonstrate 3D diffractive optics showing this multiplexing effect. According to this new phenomenon, multiple pages of information are encoded and can be read out across independent channels by rotating one or more diffractive layers with respect to the others. We implement the concept with multilayer diffractive optical elements. An iterative projection optimization algorithm helps solve the inverse design problem. The experimental realization using photolithographically fabricated multilevel phase layers demonstrates the predicted performance. We discuss the limitations and potential of azimuthal multiplexing 3D diffractive optics. Multiplexing ; Holography ; Diffraction ; Azimuth ; Optics ; Computer-generated holography ; Computer science ; Physics ; Spatial light modulator ; Telecommunications Metamaterials and Metasurfaces Applications ; Advanced Optical Imaging Technologies ; Orbital Angular Momentum in Optics
Authors: Maen Takruri | Abubakar Abubakar | Noora Alnaqbi | Hessa Al Shehhi | Abdul-Halim Jallad | Amine Bermak
Source: IEEE Access (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor Good nutrition is an important part of leading a healthy lifestyle. This has brought into stark focus the need for efficient and low-cost methods for large scale food quality assessment. This article proposes a non-invasive and non-destructive system for estimating the freshness of apples using polarization images from a Division-of-Focal-Plane (DoFP) polarization camera. The proposed system uses Machine Learning Systems namely, Support Vector Regression (SVR) and Gaussian Process Regression (GPR), to estimate the age of apples and determine if they are fit for consumption even before the external rot appears on the fruit. Initially, the reconstructed images namely, Degree of Linear Polarization (DoLP) and Angle of Polarization (AoP), are generated from the polarization image and their respective correlations with the actual age of apples (in days) are established. These reconstructed images are then fed as input features to the Machine Learning Systems to ultimately estimate the age of the apples. Experiments on real data obtained from the DoFP camera show that the proposed system is non-destructive and capable of non-invasively estimating the age of the apple with an average accuracy of up to 92.57%. Artificial intelligence ; Support vector machine ; Computer science ; Kriging ; Polarization (electrochemistry) ; Linear regression ; Gaussian process ; Machine learning ; Computer vision ; Gaussian ; Physics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Optical Polarization and Ellipsometry
Authors: R. Patrick Xian | Yves Acremann | Steinn Y. Agustsson | Maciej Dendzik | Kevin Bühlmann | Davide Curcio | Dmytro Kutnyakhov | Federico Pressacco | Michael Heber | Shuo Dong | Tommaso Pincelli | Jure Demsar | Wilfried Wurth | Philip Hofmann | Martin Wolf | Markus Scheidgen | Laurenz Rettig | Ralph Ernstorfer
Source: Scientific Data (article, 2020-12-17)
Field: Materials Science — Materials Chemistry

An open-source, end-to-end workflow for multidimensional photoemission spectroscopy Characterization of the electronic band structure of solid state materials is routinely performed using photoemission spectroscopy. Recent advancements in short-wavelength light sources and electron detectors give rise to multidimensional photoemission spectroscopy, allowing parallel measurements of the electron spectral function simultaneously in energy, two momentum components and additional physical parameters with single-event detection capability. Efficient processing of the photoelectron event streams at a rate of up to tens of megabytes per second will enable rapid band mapping for materials characterization. We describe an open-source workflow that allows user interaction with billion-count single-electron events in photoemission band mapping experiments, compatible with beamlines at 3<sup>rd</sup> and 4<sup>rd</sup> generation light sources and table-top laser-based setups. The workflow offers an end-to-end recipe from distributed operations on single-event data to structured formats for downstream scientific tasks and storage to materials science database integration. Both the workflow and processed data can be archived for reuse, providing the infrastructure for documenting the provenance and lineage of photoemission data for future high-throughput experiments. Workflow ; Angle-resolved photoemission spectroscopy ; Inverse photoemission spectroscopy ; Photoemission spectroscopy ; X-ray photoelectron spectroscopy ; Characterization (materials science) ; Detector ; Electron Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications ; Electronic and Structural Properties of Oxides
Authors: Kamila Zdybał | E. F. ARMSTRONG | Alessandro Parente | James C. Sutherland
Source: SoftwareX (article, 2020-07-01)
Field: Chemistry — Analytical Chemistry

PCAfold: Python software to generate, analyze and improve PCA-derived low-dimensional manifolds Many scientific disciplines rely on dimensionality reduction techniques for computationally less expensive handling of multivariate data sets. In particular, Principal Component Analysis (PCA) is a popular method that can be used to discover the underlying low-dimensional manifolds in high-dimensional data sets. PCA-derived manifolds are formed by projecting the original data set onto a new basis spanned by the first few Principal Components (PCs). In many cases, it is crucial that the manifold maintains certain topological characteristics for its subsequent analysis and parameterization. Avoiding overlap or steep gradients of a dependent variable could be two desired examples. In this paper, we present PCAfold, a Python software package that can be used to generate, improve and analyze low-dimensional manifolds. Our software incorporates data preprocessing, clustering and sampling techniques, uses PCA as a data reduction technique and utilizes a novel approach to assess the quality of the obtained low-dimensional manifolds. Python (programming language) ; Principal component analysis ; Dimensionality reduction ; Computer science ; Preprocessor ; Software ; Nonlinear dimensionality reduction ; Data mining ; Cluster analysis ; Manifold (fluid mechanics) ; Curse of dimensionality ; Data reduction ; Multivariate statistics ; Algorithm ; Artificial intelligence ; Machine learning Spectroscopy and Chemometric Analyses ; Face and Expression Recognition ; Sensory Analysis and Statistical Methods
Authors: Ibrahim Chamseddine | Hermann B. Frieboes | Michael Kokkolaras
Source: Scientific Reports (article, 2020-05-19)
Field: Materials Science — Biomaterials

Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles The pharmacokinetics of nanoparticle-borne drugs targeting tumors depends critically on nanoparticle design. Empirical approaches to evaluate such designs in order to maximize treatment efficacy are time- and cost-intensive. We have recently proposed the use of computational modeling of nanoparticle-mediated drug delivery targeting tumor vasculature coupled with numerical optimization to pursue optimal nanoparticle targeting and tumor uptake. Here, we build upon these studies to evaluate the effect of tumor size on optimal nanoparticle design by considering a cohort of heterogeneously-sized tumor lesions, as would be clinically expected. The results indicate that smaller nanoparticles yield higher tumor targeting and lesion regression for larger-sized tumors. We then augment the nanoparticle design optimization problem by considering drug diffusivity, which yields a two-fold tumor size decrease compared to optimizing nanoparticles without this consideration. We quantify the tradeoff between tumor targeting and size decrease using bi-objective optimization, and generate five Pareto-optimal nanoparticle designs. The results provide a spectrum of treatment outcomes - considering tumor targeting vs. antitumor effect - with the goal to enable therapy customization based on clinical need. This approach could be extended to other nanoparticle-based cancer therapies, and support the development of personalized nanomedicine in the longer term. Nanomedicine ; Nanoparticle ; Drug delivery ; Computer science ; Nanotechnology ; Materials science Nanoparticle-Based Drug Delivery ; Mathematical Biology Tumor Growth ; 3D Printing in Biomedical Research
Authors: H. J. Bernstein | Andreas Förster | Asmit Bhowmick | Aaron S. Brewster | Sándor Brockhauser | Luca Gelisio | David R. Hall | Filip Leonarski | Valerio Mariani | Gianluca Santoni | Clemens Vonrhein | Graeme Winter
Source: IUCrJ (article, 2020-07-10)
Field: Materials Science — Materials Chemistry

Gold Standard for macromolecular crystallography diffraction data Macromolecular crystallography (MX) is the dominant means of determining the three-dimensional structures of biological macromolecules. Over the last few decades, most MX data have been collected at synchrotron beamlines using a large number of different detectors produced by various manufacturers and taking advantage of various protocols and goniometries. These data came in their own formats: sometimes proprietary, sometimes open. The associated metadata rarely reached the degree of completeness required for data management according to Findability, Accessibility, Interoperability and Reusability (FAIR) principles. Efforts to reuse old data by other investigators or even by the original investigators some time later were often frustrated. In the culmination of an effort dating back more than two decades, a large portion of the research community concerned with high data-rate macromolecular crystallography (HDRMX) has now agreed to an updated specification of data and metadata for diffraction images produced at synchrotron light sources and X-ray free-electron lasers (XFELs). This 'Gold Standard' will facilitate the processing of data sets independent of the facility at which they were collected and enable data archiving according to FAIR principles, with a particular focus on interoperability and reusability. This agreed standard builds on the NeXus/HDF5 NXmx application definition and the International Union of Crystallo-graphy (IUCr) imgCIF/CBF dictionary, and it is compatible with major data-processing programs and pipelines. Just as with the IUCr CBF/imgCIF standard from which it arose and to which it is tied, the NeXus/HDF5 NXmx Gold Standard application definition is intended to be applicable to all detectors used for crystallography, and all hardware and software developers in the field are encouraged to adopt and contribute to the standard. X-ray crystallography ; Computer science ; Macromolecule ; Chemistry ; Diffraction ; Crystallography ; Biochemistry ; Physics Enzyme Structure and Function ; Advanced X-ray Imaging Techniques ; X-ray Spectroscopy and Fluorescence Analysis
Authors: Juan M. Sánchez
Source: Journal of Separation Science (article, 2020-04-06)
Field: Chemistry — Spectroscopy

Linear calibrations in chromatography: The incorrect use of ordinary least squares for determinations at low levels, and the need to redefine the limit of quantification with this regression model Ordinary least squares is widely applied as the standard regression method for analytical calibrations, and it is usually accepted that this regression method can be used for quantification starting at the limit of quantification. However, it requires calibration being homoscedastic and this is not common. Different calibrations have been evaluated to assess whether ordinary least squares is adequate to quantify estimates at low levels. All calibrations evaluated were linear and heteroscedastic. Despite acceptable values for precision at limit of quantification levels were obtained, ordinary least squares fitting resulted in significant and unacceptable bias at low levels. When weighted least squares regression was applied, bias at low levels was solved and accurate estimates were obtained. With heteroscedastic calibrations, limit values determined by conventional methods are only appropriate if weighted least squares are used. A "practical limit of quantification" can be determined with ordinary least squares in heteroscedastic calibrations, which should be fixed at a minimum of 20 times the value calculated with conventional methods. Biases obtained above this "practical limit" were acceptable applying ordinary least squares and no significant differences were obtained between the estimates measured using weighted and ordinary least squares when analyzing real-world samples. Ordinary least squares ; Homoscedasticity ; Heteroscedasticity ; Least-squares function approximation ; Mathematics ; Non-linear least squares ; Statistics ; Calibration ; Total least squares ; Generalized least squares ; Linear regression ; Explained sum of squares ; Partial least squares regression ; Regression analysis Analytical Chemistry and Chromatography ; Pesticide Residue Analysis and Safety ; Spectroscopy and Chemometric Analyses
Authors: Hyungki Shim | Haejun Chung | Owen D. Miller
Source: Physical Review Applied (article, 2020-07-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Maximal Free-Space Concentration of Electromagnetic Waves Concentrating free-space optical beams onto arbitrarily small spots is of immense interest for applications from imaging to 3D printing, but the extent to which light concentration below the diffraction limit can be achieved is still unclear. This study establishes upper bounds on light concentration for any beam-shaping device, and uses inverse design to discover structures operating near these limits. These bounds can serve as guideposts for future designs operating at ultrahigh resolution. Limit (mathematics) ; Diffraction ; Inverse ; Electromagnetic radiation ; Upper and lower bounds ; Inverse problem Metamaterials and Metasurfaces Applications ; Electromagnetic Scattering and Analysis ; Plasmonic and Surface Plasmon Research
Authors: Selena J. Lockyer | Selina Nawaz | Adam Brookfield | Alistair J. Fielding | Íñigo J. Vitórica‐Yrezábal | Grigore A. Timco | Neil A. Burton | Alice M. Bowen | Richard E. P. Winpenny | Eric J. L. McInnes
Source: Journal of the American Chemical Society (article, 2020-08-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Conformational Flexibility of Hybrid [3]- and [4]-Rotaxanes The synthesis, structures, and properties of [4]- and [3]-rotaxane complexes are reported where [2]-rotaxanes, formed from heterometallic {Cr<sub>7</sub>Ni} rings, are bound to a fluoride-centered {CrNi<sub>2</sub>} triangle. The compounds have been characterized by single-crystal X-ray diffraction and have the formulas [CrNi<sub>2</sub>(F)(O<sub>2</sub>C<sup>t</sup>Bu)<sub>6</sub>]{(<b>B</b>H)[Cr<sub>7</sub>NiF<sub>8</sub>(O<sub>2</sub>C<sup>t</sup>Bu)<sub>16</sub>]}<sub>3</sub> (<b>3</b>) and [CrNi<sub>2</sub>(F)(O<sub>2</sub>C<sup>t</sup>Bu)<sub>6</sub>(THF)]{(<b>B</b>H)[Cr<sub>7</sub>NiF<sub>8</sub>(O<sub>2</sub>C<sup>t</sup>Bu)<sub>16</sub>]}<sub>2</sub> (<b>4</b>), where <b>B</b> = py-CH<sub>2</sub>CH<sub>2</sub>NHCH<sub>2</sub>C<sub>6</sub>H<sub>4</sub>SCH<sub>3</sub>. The [4]-rotaxane <b>3</b> is an isosceles triangle of three [2]-rotaxanes bound to the central triangle while the [3]-rotaxane <b>4</b> contains only two [2]-rotaxanes bound to the central triangle. Studies of the behavior of <b>3</b> and <b>4</b> in solution by small-angle X-ray scattering and atomistic molecular dynamic simulations show that the structure of <b>3</b> is similar to that found in the crystal but that <b>4</b> has a different conformation to the crystal. Continuous wave and pulsed electron paramagnetic resonance spectroscopy was used to study the structures present and demonstrate that in frozen solutions (at 5 K) <b>4</b> forms more extended molecules than <b>3</b> and with a wider range of conformations. Rotaxane ; Chemistry ; Crystallography ; Molecule ; Isosceles triangle ; Electron paramagnetic resonance ; Crystal (programming language) ; Crystal structure ; Stereochemistry ; Supramolecular chemistry ; Nuclear magnetic resonance ; Geometry Magnetism in coordination complexes ; Electron Spin Resonance Studies ; Lanthanide and Transition Metal Complexes
Authors: Grigorii Drozdov | Igor Ostanin | Hao Xu | Yuezhou Wang | Traian Dumitrică | Artem Grebenko | Alexey P. Tsapenko | Yuriy Gladush | Georgy Ermolaev | Valentyn S. Volkov | Sebastian Eibl | Ulrich Rüde | Albert G. Nasibulin
Source: Journal of Applied Physics (article, 2020-11-09)
Field: Materials Science — Materials Chemistry

Densification of single-walled carbon nanotube films: Mesoscopic distinct element method simulations and experimental validation Nanometer-thin single-walled carbon nanotube (CNT) films collected from the aerosol chemical deposition reactors have gathered attention for their promising applications. Densification of these pristine films provides an important way to manipulate mechanical, electronic, and optical properties. To elucidate the underlying microstructural level restructuring, which is ultimately responsible for the change in properties, we perform large scale vector-based mesoscopic distinct element method simulations in conjunction with electron microscopy and spectroscopic ellipsometry characterization of pristine and densified films by drop-cast volatile liquid processing. Matching with the microscopy observations, pristine CNT films with a finite thickness are modeled as self-assembled CNT networks comprising entangled dendritic bundles with branches extending down to individual CNTs. Simulations of these films under uniaxial compression uncover a soft deformation regime extending up to an ∼75% strain. When removing the loads, the pre-compressed samples evolve into homogeneously densified films with thickness values depending on both the pre-compression level and the sample microstructure. The significant reduction in thickness is attributed to the underlying structural changes occurring at the 100 nm scale, including the zipping of the thinnest dendritic branches. Mesoscopic physics ; Carbon nanotube ; Deformation (meteorology) ; Characterization (materials science) ; Deposition (geology) ; Finite element method ; Carbon fibers ; Compression (physics) ; Scanning electron microscope Carbon Nanotubes in Composites ; Chemical and Physical Properties of Materials ; Anodic Oxide Films and Nanostructures