jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sae Dieb | Zhufeng Hou | Koji Tsuda
Source: The Journal of Chemical Physics (article, 2018-03-19)
Field: Materials Science — Materials Chemistry

Structure prediction of boron-doped graphene by machine learning Heteroatom doping has endowed graphene with manifold aspects of material properties and boosted its applications. The atomic structure determination of doped graphene is vital to understand its material properties. Motivated by the recently synthesized boron-doped graphene with relatively high concentration, here we employ machine learning methods to search the most stable structures of doped boron atoms in graphene, in conjunction with the atomistic simulations. From the determined stable structures, we find that in the free-standing pristine graphene, the doped boron atoms energetically prefer to substitute for the carbon atoms at different sublattice sites and that the para configuration of boron-boron pair is dominant in the cases of high boron concentrations. The boron doping can increase the work function of graphene by 0.7 eV for a boron content higher than 3.1%. Graphene ; Boron ; Heteroatom ; Doping ; Materials science ; Chemical physics ; Carbon fibers ; Nanotechnology ; Optoelectronics ; Chemistry ; Composite material ; Organic chemistry ; Composite number Graphene research and applications ; Machine Learning in Materials Science ; Advancements in Battery Materials
Authors: Elisa Jimenez‐Izal | Anastassia N. Alexandrova
Source: Annual Review of Physical Chemistry (article, 2018-02-28)
Field: Materials Science — Materials Chemistry

Computational Design of Clusters for Catalysis When small clusters are studied in chemical physics or physical chemistry, one perhaps thinks of the fundamental aspects of cluster electronic structure, or precision spectroscopy in ultracold molecular beams. However, small clusters are also of interest in catalysis, where the cold ground state or an isolated cluster may not even be the right starting point. Instead, the big question is: What happens to cluster-based catalysts under real conditions of catalysis, such as high temperature and coverage with reagents? Myriads of metastable cluster states become accessible, the entire system is dynamic, and catalysis may be driven by rare sites present only under those conditions. Activity, selectivity, and stability are highly dependent on size, composition, shape, support, and environment. To probe and master cluster catalysis, sophisticated tools are being developed for precision synthesis, operando measurements, and multiscale modeling. This review intends to tell the messy story of clusters in catalysis. Cluster (spacecraft) ; Catalysis ; Metastability ; Nanotechnology ; Chemical physics ; Heterogeneous catalysis ; Spectroscopy ; Chemistry ; Physics ; Materials science ; Computer science ; Organic chemistry ; Quantum mechanics Catalytic Processes in Materials Science ; Nanocluster Synthesis and Applications ; 2D Materials and Applications
Authors: Chu Zhang | Fei Liu | Yong He
Source: Scientific Reports (article, 2018-01-26)
Field: Chemistry — Analytical Chemistry

Identification of coffee bean varieties using hyperspectral imaging: influence of preprocessing methods and pixel-wise spectra analysis Hyperspectral imaging was used to identify and to visualize the coffee bean varieties. Spectral preprocessing of pixel-wise spectra was conducted by different methods, including moving average smoothing (MA), wavelet transform (WT) and empirical mode decomposition (EMD). Meanwhile, spatial preprocessing of the gray-scale image at each wavelength was conducted by median filter (MF). Support vector machine (SVM) models using full sample average spectra and pixel-wise spectra, and the selected optimal wavelengths by second derivative spectra all achieved classification accuracy over 80%. Primarily, the SVM models using pixel-wise spectra were used to predict the sample average spectra, and these models obtained over 80% of the classification accuracy. Secondly, the SVM models using sample average spectra were used to predict pixel-wise spectra, but achieved with lower than 50% of classification accuracy. The results indicated that WT and EMD were suitable for pixel-wise spectra preprocessing. The use of pixel-wise spectra could extend the calibration set, and resulted in the good prediction results for pixel-wise spectra and sample average spectra. The overall results indicated the effectiveness of using spectral preprocessing and the adoption of pixel-wise spectra. The results provided an alternative way of data processing for applications of hyperspectral imaging in food industry. Hyperspectral imaging ; Pixel ; Pattern recognition (psychology) ; Preprocessor ; Artificial intelligence ; Support vector machine ; Smoothing ; Spectral line ; Computer science ; Principal component analysis ; Data pre-processing ; Mathematics ; Computer vision ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Tuğba Yıldız | Renpeng Gu | Stefan Zauscher | Tania Betancourt
Source: International Journal of Nanomedicine (article, 2018-10-01)
Field: Materials Science — Biomaterials

Doxorubicin-loaded protease-activated near-infrared fluorescent polymeric nanoparticles for imaging and therapy of cancer Doxorubicin-loaded, enzymatically activatable nanoparticles of less than 100 nm were prepared successfully by nanoprecipitation of copolymer blends. These nanoparticles were found to be suitable as controlled drug delivery systems and contrast agents for imaging of cancer cells. Doxorubicin ; Materials science ; Fluorescence ; Cancer therapy ; Nanoparticle ; Nanotechnology ; Biophysics ; Cancer ; Biomedical engineering ; Chemotherapy ; Medicine ; Surgery ; Optics ; Internal medicine Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Graphene and Nanomaterials Applications
Authors: De‐Wei Gao | Ekaterina V. Vinogradova | Sri Krishna Nimmagadda | Jose M. Medina | Yiyang Xiao | Radu M. Suciu | Benjamin F. Cravatt | Keary M. Engle
Source: Journal of the American Chemical Society (article, 2018-06-12)
Field: Chemistry — Organic Chemistry

Direct Access to Versatile Electrophiles via Catalytic Oxidative Cyanation of Alkenes Nucleophilic attack on carbon-based electrophiles is a central reactivity paradigm in chemistry and biology. The steric and electronic properties of the electrophile dictate its reactivity with different nucleophiles of interest, allowing the opportunity to fine-tune electrophiles for use as coupling partners in multistep organic synthesis or for covalent modification of proteins in drug discovery. Reactions that directly transform inexpensive chemical feedstocks into versatile carbon electrophiles would therefore be highly enabling. Herein, we report the catalytic, regioselective oxidative cyanation of conjugated and nonconjugated alkenes using a homogeneous copper catalyst and a bystanding N-F oxidant to furnish branched alkenyl nitriles that are difficult to prepare using existing methods. We show that the alkenyl nitrile products serve as electrophilic reaction partners for both organic synthesis and the chemical proteomic discovery of covalent protein ligands. Chemistry ; Cyanation ; Electrophile ; Catalysis ; Oxidative phosphorylation ; Combinatorial chemistry ; Organic chemistry ; Biochemistry Catalytic C–H Functionalization Methods ; Synthesis and Catalytic Reactions ; Advanced Synthetic Organic Chemistry
Authors: Linglong Li | Yaodong Yang | Dawei Zhang | Zuo‐Guang Ye | Stephen Jesse | Sergei V. Kalinin | Rama K. Vasudevan
Source: Science Advances (article, 2018-03-02)
Field: Materials Science — Materials Chemistry

Machine learning–enabled identification of material phase transitions based on experimental data: Exploring collective dynamics in ferroelectric relaxors Exploration of phase transitions and construction of associated phase diagrams are of fundamental importance for condensed matter physics and materials science alike, and remain the focus of extensive research for both theoretical and experimental studies. For the latter, comprehensive studies involving scattering, thermodynamics, and modeling are typically required. We present a new approach to data mining multiple realizations of collective dynamics, measured through piezoelectric relaxation studies, to identify the onset of a structural phase transition in nanometer-scale volumes, that is, the probed volume of an atomic force microscope tip. Machine learning is used to analyze the multidimensional data sets describing relaxation to voltage and thermal stimuli, producing the temperature-bias phase diagram for a relaxor crystal without the need to measure (or know) the order parameter. The suitability of the approach to determine the phase diagram is shown with simulations based on a two-dimensional Ising model. These results indicate that machine learning approaches can be used to determine phase transitions in ferroelectrics, providing a general, statistically significant, and robust approach toward determining the presence of critical regimes and phase boundaries. Ferroelectricity ; Identification (biology) ; Phase transition ; Dynamics (music) ; Phase (matter) ; Materials science ; Computer science ; Condensed matter physics ; Nanotechnology ; Statistical physics ; Chemical physics ; Physics ; Optoelectronics Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Acoustic Wave Resonator Technologies
Authors: Jurn Heinen | David Dubbeldam
Source: Wiley Interdisciplinary Reviews Computational Molecular Science (review, 2018-03-25)
Field: Chemistry — Inorganic Chemistry

On flexible force fields for metal–organic frameworks: Recent developments and future prospects Classical force field simulations can be used to study structural, diffusion, and adsorption properties of metal-organic frameworks (MOFs). To account for the dynamic behavior of the material, parameterization schemes have been developed to derive force constants and the associated reference values by fitting on ab initio energies, vibrational frequencies, and elastic constants. Here, we review recent developments in flexible force field models for MOFs. Existing flexible force field models are generally able to reproduce the majority of experimentally observed structural and dynamic properties of MOFs. The lack of efficient sampling schemes for capturing stimuli-driven phase transitions, however, currently limits the full predictive potential of existing flexible force fields from being realized. This article is categorized under: Structure and Mechanism > Computational Materials ScienceMolecular and Statistical Mechanics > Molecular Mechanics. Force field (fiction) ; Force constant ; Statistical physics ; Field (mathematics) ; Molecular dynamics ; Statistical mechanics ; Ab initio ; Computer science ; Nanotechnology ; Materials science ; Classical mechanics ; Computational chemistry ; Physics ; Chemistry ; Molecule ; Mathematics ; Quantum mechanics ; Artificial intelligence Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Crystallography and molecular interactions
Authors: Yulong Fan | Yunkun Xu | Meng Qiu | Wei Jin | Lei Zhang | Edmund Y. Lam | Din Ping Tsai | Dangyuan Lei
Source: Nanophotonics (article, 2018-06-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Phase‐controlled metasurface design via optimized genetic algorithm Abstract In an optical Pancharatnam‐Berry (PB) phase metasurface, each sub‐wavelength dielectric structure of varied spatial orientation can be treated as a point source with the same amplitude yet varied relative phase. In this work, we introduce an optimized genetic algorithm (GA) method for the synthesis of one‐dimensional (1D) PB phase‐controlled dielectric metasurfaces by seeking for optimized phase profile solutions, which differs from previously reported amplitude‐controlled GA method only applicable to generate transverse optical modes with plasmonic metasurfaces. The GA–optimized phase profiles can be readily used to construct dielectric metasurfaces with improved functionalities. The loop of phase‐controlled GA consists of initialization, random mutation, screened evolution, and duplication. Here random mutation is realized by changing the phase of each unit cell, and this process should be efficient to obtain enough mutations to drive the whole GA process under supervision of appropriate mutation boundary. A well‐chosen fitness function ensures the right direction of screened evolution, and the duplication process guarantees an equilibrated number of generated light patterns. Importantly, we optimize the GA loop by introducing a multi‐step hierarchical mutation process to break local optimum limits. We demonstrate the validity of our optimized GA method by generating longitudinal optical modes (i. e., non‐diffractive light sheets) with 1D PB phase dielectric metasurfaces having non‐analytical counter‐intuitive phase profiles. The produced large‐area, long‐distance light sheets could be used for realizing high‐speed, low‐noise light‐sheet microscopy. Additionally, a simplified 3D light pattern generated by a 2D PB phase metasurface further reveals the potential of our optimized GA method for manipulating truly 3D light fields. Phase (matter) ; Optics ; Initialization ; Dielectric ; Genetic algorithm ; Plasmon ; Materials science ; Algorithm ; Computer science ; Optoelectronics ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Plasmonic and Surface Plasmon Research
Authors: Jianguo Cai | Yanyang Zhang | Yue Qian | Chao Shan | Bingcai Pan
Source: Scientific Reports (article, 2018-07-31)
Field: Materials Science — Materials Chemistry

Enhanced Defluoridation Using Novel Millisphere Nanocomposite of La-Doped Li-Al Layered Double Hydroxides Supported by Polymeric Anion Exchanger A novel nanocomposite bead LaLiAl-LDH@201 was fabricated by doping a small amount of La into nanocrystalline Li/Al layered double hydroxides (LDHs) pre-confined inside polystyrene anion exchanger D201 (LiAl-LDH@201). A systematic characterisation of the resultant LaLiAl-LDH@201 (XRD, SEM-EDS, TEM-EDS, and XPS) evidenced the successful incorporation of La into the Li/Al LDHs, with their interlayer distance expanded to allow more exchangeable sites for fluoride uptake. The resultant LaLiAl-LDH@201 showed high and stable defluoridation performance over a wide range of pH from 4 to 9. The superior uptake capacity and affinity for fluoride of LaLiAl-LDH@201 over LiAl-LDH@201 were driven by both the increased anion exchange capacity of the embedded LDHs and the specific La-F interaction evidenced via XPS and TEM-EDS characterisation. Fixed-bed column test confirmed that the working capacity of LaLiAl-LDH@201 for defluoridation of authentic fluoride-rich groundwater was nearly twice that of LiAl-LDH@201. The fluoride-loaded LaLiAl-LDH@201 could be conveniently regenerated in situ by using NaOH + NaCl binary solution, achieving desorption efficiency above 98%. Moreover, negligible capacity loss, La leaching, or structure alteration was observed after five adsorption-regeneration cycles, indicating the high stability of LaLiAl-LDH@201. Therefore, the novel millisphere nanocomposite LaLiAl-LDH@201 was promising for efficient defluoridation from water and wastewater. Nanocomposite ; Layered double hydroxides ; Ion exchange ; Anion exchanger ; Doping ; Chemical engineering ; Materials science ; Ion ; Polymer chemistry ; Nuclear chemistry ; Chemistry ; Inorganic chemistry ; Composite material ; Adsorption ; Organic chemistry Layered Double Hydroxides Synthesis and Applications ; Fluoride Effects and Removal ; Inorganic Fluorides and Related Compounds
Authors: Zemeng Lin | Xiaowei Li | Rongxuan Zhao | Xu Song | Yongtian Wang | Lingling Huang
Source: Nanophotonics (article, 2018-06-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

High‐efficiency Bessel beam array generation by Huygens metasurfaces Abstract Bessel beams have attracted considerable interest because of their unique non‐diffractive, self‐healing characteristics. Different approaches have been proposed to generate Bessel beams, such as using axicons, diffractive optical elements, composite holograms, or spatial light modulators. However, these approaches have suffered from limited numerical aperture, low efficiency, polarization‐dependent properties, etc. Here, by utilizing dielectric Huygens metasurfaces as ultrathin, compact platforms by integrating the functionalities of Dammann gratings and axicons, we successfully demonstrate multiple Bessel beam generation with polarization‐independent property. The number of two‐dimensional arrays can be controlled flexibly, which can enhance information capacity with a total efficiency that can reach 66.36%. This method can have various applications, such as parallel laser fabrication, efficient optical tweezers, and optical communication. Bessel beam ; Optics ; Bessel function ; Optical tweezers ; Dielectric ; Holography ; Polarization (electrochemistry) ; Materials science ; Diffraction efficiency ; Diffraction ; Grating ; Optoelectronics ; Laser ; Numerical aperture ; Spatial light modulator ; Fabrication ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Kaimin Du | Xia Xu | Shuang Yao | Pengpeng Lei | Lile Dong | Manli Zhang | Jing Feng | Hongjie Zhang
Source: CrystEngComm (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Enhanced upconversion luminescence and controllable phase/shape of NaYF<sub>4</sub>:Yb/Er crystals through Cu<sup>2+</sup> ion doping The crystal phase/shape and upconversion luminescence properties of NaYF<sub>4</sub>:Yb/Er crystals could be fine-tuned through doping with Cu<sup>2+</sup> ions. Photon upconversion ; Luminescence ; Materials science ; Doping ; Ion ; Crystal (programming language) ; Phase (matter) ; Ytterbium ; Analytical Chemistry (journal) ; Optoelectronics ; Chemistry Luminescence Properties of Advanced Materials ; Solid State Laser Technologies ; Inorganic Fluorides and Related Compounds
Authors: José A. Heredia‐Guerrero | Luca Ceseracciu | Susana Guzmán‐Puyol | Uttam C. Paul | Alejandro Alfaro-Pulido | Chiara Grande | Luigi Vezzulli | Tiziano Bandiera | Rosalia Bertorelli | Debora Russo | Athanassia Athanassiou | Ilker S. Bayer
Source: Carbohydrate Polymers (article, 2018-03-18)
Field: Chemistry — Organic Chemistry

Antimicrobial, antioxidant, and waterproof RTV silicone-ethyl cellulose composites containing clove essential oil Polydimethylsiloxane ; Composite number ; Essential oil ; Ethyl cellulose ; Antimicrobial ; Cellulose ; Materials science ; Composite material ; Silicone oil ; Polymer ; Chemistry ; Antioxidant ; Silicone ; Chemical engineering ; Organic chemistry ; Food science Antimicrobial agents and applications ; Nanocomposite Films for Food Packaging ; Essential Oils and Antimicrobial Activity
Authors: Guodong Qi | Qiang Wang | Jun Xu | Qinming Wu | Chao Wang | Xingling Zhao | Xiangju Meng | Feng‐Shou Xiao | Feng Deng
Source: Communications Chemistry (article, 2018-04-19)
Field: Chemistry — Spectroscopy

Direct observation of tin sites and their reversible interconversion in zeolites by solid-state NMR spectroscopy Abstract Metal-substituted zeolites are an important type of solid Lewis acid with a wide range of applications. Despite the importance of this type of catalyst, identifying active sites can be challenging because different types of metal sites experience similar environments in zeolites. Here we show direct observation of different tin sites in Sn-β zeolite. Two types of open tin sites are unambiguously identified via correlating the hydroxyl groups to Sn atoms with one- and two-dimensional proton-detected 1 H/ 119 Sn correlation solid-state NMR spectroscopy, which only amounts to ca. 17% of the total tin content. A reversible transformation between the open and closed tin site is observed. The results provide valuable insights into the nature of tin sites in Sn-β zeolite and open an avenue for the use of proton-detected solid-state NMR methods for characterization of metal sites in zeolite catalysts. Tin ; Zeolite ; Solid-state nuclear magnetic resonance ; Catalysis ; Chemistry ; Metal ; Nuclear magnetic resonance spectroscopy ; Spectroscopy ; Inorganic chemistry ; Proton ; Solid-state ; Physical chemistry ; Nuclear magnetic resonance ; Organic chemistry ; Physics Advanced NMR Techniques and Applications ; Advanced Battery Materials and Technologies ; Zeolite Catalysis and Synthesis
Authors: Natalia Gorenkova | Ibrahim Osama | F. Philipp Seib | H Carswell
Source: ACS Biomaterials Science & Engineering (article, 2018-11-27)
Field: Materials Science — Biomaterials

In Vivo Evaluation of Engineered Self-Assembling Silk Fibroin Hydrogels after Intracerebral Injection in a Rat Stroke Model Targeting the brain cavity formed by an ischemic stroke is appealing for many regenerative treatment strategies but requires a robust delivery technology. We hypothesized that self-assembling silk fibroin hydrogels could serve as a reliable support matrix for regeneration in the stroke cavity. We therefore performed in vivo evaluation studies of self-assembling silk fibroin hydrogels after intracerebral injection in a rat stroke model. Adult male Sprague-Dawley rats (<i>n</i> = 24) underwent transient middle cerebral artery occlusion (MCAo) 2 weeks before random assignment to either no stereotaxic injection or a stereotaxic injection of either self-assembling silk fibroin hydrogels (4% w/v) or PBS into the lesion cavity. The impact on morbidity and mortality, space conformity, interaction with glial scar, interference with inflammatory response, and cell proliferation in the lesion cavity were examined for up to 7 weeks by a blinded investigator. Self-assembling hydrogels filled the stroke cavity with excellent space conformity and presented neither an overt microglial/macrophage response nor an adverse morbidity or mortality. The relationship between the number of proliferating cells and lesion volume was significantly changed by injection of self-assembling silk hydrogels. This in vivo stroke model confirmed that self-assembling silk fibroin hydrogels provide a favorable microenvironment as a future support matrix in the stroke cavity. Fibroin ; Self-healing hydrogels ; In vivo ; Stroke (engine) ; Biomedical engineering ; Medicine ; Lesion ; Materials science ; SILK ; Pathology ; Biology ; Polymer chemistry Silk-based biomaterials and applications ; Nerve injury and regeneration ; RNA Interference and Gene Delivery