jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Consuelo J. Perez | Aafreen K. Bagga | Shamina Saiyara Prova | Maryam Yousefi‐Taemeh | Demian R. Ifa
Source: Rapid Communications in Mass Spectrometry (article, 2018-04-26)
Field: Chemistry — Spectroscopy

Review and perspectives on the applications of mass spectrometry imaging under ambient conditions Ambient mass spectrometry (AMS)-based techniques are performed under ambient conditions in which the ionization and desorption occur in the open environment allowing the direct analysis of molecules with minimal or no sample preparation. A selected group of AMS techniques demonstrate imaging capabilities that can provide information about the localization of molecules on complex sample surfaces such as biological tissues. 2D, 3D, and multimodal imaging have unlocked an array of applications to systematically address complex problems in many areas of research such as drug monitoring, natural products, forensics, and cancer diagnostics. In the present review, we summarize recent advances in the field with respect to the implementation of new ambient ionization techniques and current applications in the last 5 years. In more detail, we mainly focus on imaging applications in topics related to animal whole bodies and tissues, single cells, cancer diagnostics and biomarkers, microbial cultures and co-cultures, plant and natural product metabolomics, and forensic applications. Finally, we discuss new areas of research, future perspectives, and the overall direction that the field may take in the years to come. Mass spectrometry imaging ; Chemistry ; Mass spectrometry ; Nanotechnology ; Ambient ionization ; Metabolomics ; Sample (material) ; Sample preparation ; Computational biology ; Data science ; Environmental chemistry ; Ionization ; Biochemical engineering ; Computer science ; Chromatography ; Chemical ionization ; Materials science ; Organic chemistry Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Ion-surface interactions and analysis
Authors: Weiliang Mei | Yang Du | Tangyan Wu | Feng Gao | Bin Wang | Jingui Duan | Junjing Zhou | Rongfei Zhou
Source: Journal of Membrane Science (article, 2018-08-22)
Field: Chemistry — Inorganic Chemistry

High-flux CHA zeolite membranes for H2 separations Permeance ; Membrane ; Selectivity ; Zeolite ; Chemical engineering ; Chemistry ; Pressure drop ; Permeability (electromagnetism) ; Permeation ; Chromatography ; Analytical Chemistry (journal) ; Materials science ; Organic chemistry ; Thermodynamics ; Catalysis Zeolite Catalysis and Synthesis ; Membrane Separation and Gas Transport ; Carbon Dioxide Capture Technologies
Authors: Timo Rhauderwiek | Haishuang Zhao | Patrick Hirschle | Markus Döblinger | Bart Bueken | Helge Reinsch | Dirk De Vos | Stefan Wuttke | Ute Kolb | Norbert Stock
Source: Chemical Science (article, 2018-01-01)
Field: Chemistry — Inorganic Chemistry

Highly stable and porous porphyrin-based zirconium and hafnium phosphonates – electron crystallography as an important tool for structure elucidation The Ni-metallated porphyrin-based tetraphosphonic acid (Ni-tetra(4-phosphonophenyl)porphyrin, Ni-H<sub>8</sub>TPPP) was used for the synthesis of highly porous metal phosphonates containing the tetravalent cations Zr<sup>4+</sup> and Hf<sup>4+</sup>. The compounds were thoroughly characterized regarding their sorption properties towards N<sub>2</sub> and H<sub>2</sub>O as well as thermal and chemical stability. During the synthesis optimization the reaction time could be substantially decreased under stirring from 24 to 3 h in glass vials. M-CAU-30, [M<sub>2</sub>(Ni-H<sub>2</sub>TPPP)(OH/F)<sub>2</sub>]·H<sub>2</sub>O (M = Zr, Hf) shows exceptionally high specific surface areas for metal phosphonates of <i>a</i><sub>BET</sub> = 1070 and 1030 m<sup>2</sup> g<sup>-1</sup> for Zr- and Hf-CAU-30, respectively, which are very close/correspond to the theoretical values of 1180 and 1030 m<sup>2</sup> g<sup>-1</sup>. CAU-30 is always obtained as mixtures with one mol ZrO<sub>2</sub>/HfO<sub>2</sub> per formula unit as proven by TEM, electron diffraction, TG and elemental analysis. Hence experimentally derived specific surface areas are 970 and 910 m<sup>2</sup> g<sup>-1</sup>, respectively. M-CAU-30 is chemically stable in the pH range 0 to 12 in HCl/NaOH and thermally up to 420 °C in air as determined by variable-temperature powder X-ray diffraction (VT-PXRD). The crystal structure of M-CAU-30 was determined by combining electron diffraction tomography for structure solution and powder X-ray diffraction data for the structure refinement. The crystal structure consists of chains of corner sharing MO<sub>6</sub> octahedra interconnected by the partly deprotonated linker molecules Ni-H<sub>2</sub>TPPP<sup>6-</sup>. Thus 1D channels with pore diameters of 1.3 × 2.0 nm are formed. The redox activity of Zr-CAU-30 was investigated by cyclic voltammetry resulting in a reversible redox process at a half-wave potential of <i>E</i><sub>1/2</sub> = -0.649 V. Hafnium ; Zirconium ; Porphyrin ; Crystallography ; Materials science ; Porosity ; Electron ; Chemistry ; Computational chemistry ; Chemical physics ; Inorganic chemistry ; Photochemistry ; Organic chemistry ; Physics ; Nuclear physics Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Chemical Synthesis and Characterization
Authors: Sourav Ghosh | Punarbasu Roy | Naiwrit Karmodak | Eluvathingal D. Jemmis | Govindasamy Mugesh
Source: Angewandte Chemie (article, 2018-02-09)
Field: Materials Science — Materials Chemistry

Nanoisozymes: Crystal‐Facet‐Dependent Enzyme‐Mimetic Activity of V<sub>2</sub>O<sub>5</sub> Nanomaterials Abstract Nanomaterials with enzyme‐like activity (nanozymes) attract significant interest owing to their applications in biomedical research. Particularly, redox nanozymes that exhibit glutathione peroxidase (GPx)‐like activity play important roles in cellular signaling by controlling the hydrogen peroxide (H 2 O 2 ) level. Herein we report, for the first time, that the redox properties and GPx‐like activity of V 2 O 5 nanozyme depends not only on the size and morphology, but also on the crystal facets exposed on the surface within the same crystal system of the nanomaterials. These results suggest that the surface of the nanomaterials can be engineered to fine‐tune their redox properties to act as “nanoisozymes” for specific biological applications. Nanomaterials ; Redox ; Hydrogen peroxide ; Facet (psychology) ; Chemistry ; Nanotechnology ; Crystal (programming language) ; Peroxidase ; Enzyme ; Materials science ; Inorganic chemistry ; Biochemistry Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Vanadium and Halogenation Chemistry
Authors: Jeehae Shin | Jihoon Kyhm | A‐Ra Hong | Jin Dong Song | Kwangyeol Lee | Hyungduk Ko | Ho Seong Jang
Source: Chemistry of Materials (article, 2018-10-03)
Field: Materials Science — Materials Chemistry

Multicolor Tunable Upconversion Luminescence from Sensitized Seed-Mediated Grown LiGdF<sub>4</sub>:Yb,Tm-Based Core/Triple-Shell Nanophosphors for Transparent Displays Red, green, blue, and natural white upconversion (UC) luminescence colors are realized from the tetragonal-structured LiGdF4-based core/triple-shell (C/T-S) upconversion nanophosphors (UCNPs) and the C/T-S UCNP-incorporated polymer composites. The LiYF4:Yb cores are used as sensitized seeds for the formation of LiGdF4:Yb,Tm UC shell followed by the growth of LiGdF4:Tb,Eu color tuning shell. Finally, LiYF4 inert shell is grown on the core/shell/shell UCNPs, and LiYF4:Yb/LiGdF4:Yb,Tm/LiGdF4:Tb,Eu/LiYF4 C/T-S UCNPs exhibit enhanced UC luminescence. The single tetragonal-phased C/T-S UCNPs exhibit blue, green, and red UC luminescence, which is attributed to the electronic transitions in Tm3+ via energy transfer UC process and Tb3+ and Eu3+ via energy migration UC process, respectively. The multicolor UC emissions, including natural white, medium aquamarine, purple, and thistle color, are created by fine-tuning of the ratio of Tb3+ and Eu3+ in the color tuning shell. The transparent polymer composites are prepared by incorporating the C/T-S UCNPs into polydimethylsiloxane, and the polymer composites also exhibit red, green, blue, and natural white light UC emissions, indicating that these multicolor tunable LiYF4:Yb/LiGdF4:Yb,Tm/LiGdF4:Tb,Eu/LiYF4 C/T-S UCNPs have potential to be applied to transparent volumetric displays. Luminescence ; Photon upconversion ; Materials science ; Tetragonal crystal system ; Shell (structure) ; Core (optical fiber) ; Optoelectronics ; Nanotechnology ; Composite material ; Chemistry ; Crystal structure ; Crystallography Luminescence Properties of Advanced Materials ; Luminescence and Fluorescent Materials ; Advanced Photocatalysis Techniques
Authors: Gaoyang Li | Xiaohua Wang | Xi Li | Aijun Yang | Mingzhe Rong
Source: Sensors (article, 2018-10-18)
Field: Materials Science — Materials Chemistry

Partial Discharge Recognition with a Multi-Resolution Convolutional Neural Network Partial discharge (PD) is not only an important symptom for monitoring the imperfections in the insulation system of a gas-insulated switchgear (GIS), but also the factor that accelerates the degradation. At present, monitoring ultra-high-frequency (UHF) signals induced by PDs is regarded as one of the most effective approaches for assessing the insulation severity and classifying the PDs. Therefore, in this paper, a deep learning-based PD classification algorithm is proposed and realized with a multi-column convolutional neural network (CNN) that incorporates UHF spectra of multiple resolutions. First, three subnetworks, as characterized by their specified designed temporal filters, frequency filters, and texture filters, are organized and then intergraded by a fully-connected neural network. Then, a long short-term memory (LSTM) network is utilized for fusing the embedded multi-sensor information. Furthermore, to alleviate the risk of overfitting, a transfer learning approach inspired by manifold learning is also present for model training. To demonstrate, 13 modes of defects considering both the defect types and their relative positions were well designed for a simulated GIS tank. A detailed analysis of the performance reveals the clear superiority of the proposed method, compared to18 typical baselines. Several advanced visualization techniques are also implemented to explore the possible qualitative interpretations of the learned features. Finally, a unified framework based on matrix projection is discussed to provide a possible explanation for the effectiveness of the architecture. Partial discharge ; Computer science ; Convolutional neural network ; Visualization ; Artificial intelligence ; Overfitting ; Transfer of learning ; Ultra high frequency ; Pattern recognition (psychology) ; Projection (relational algebra) ; Artificial neural network ; Filter (signal processing) ; Machine learning ; Data mining ; Engineering ; Computer vision ; Algorithm High voltage insulation and dielectric phenomena ; Elevator Systems and Control ; Power Transformer Diagnostics and Insulation
Authors: Lianlin Li | Tie Jun Cui
Source: Nanophotonics (article, 2018-06-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Information metamaterials – from effective media to real‐time information processing systems Abstract Metamaterials have been characterized by effective medium parameters over the past decades due to the subwavelength nature of meta‐atoms. Once the metamaterials are fabricated, their functions become fixed or tunable. Recently, the concept of digital metamaterials has been introduced, in which, for instance, the constitutive 1‐bit meta‐atom is digitalized as “0” or “1” corresponding to two opposite electromagnetic (EM) responses. The digital metamaterials set up a bridge between the physical world and the information world. More interestingly, when the digital meta‐atom is programmable, a single metamaterial can be used to realize different functions when programmed with different coding sequences. Moreover, as the states of programmable meta‐atoms can be quickly switched, it enables the wave‐based information coding and processing on the physical level of metamaterials in real time. For these reasons, we prefer to call digital metamaterials with programmable meta‐atoms as “information metamaterials.” In this review article, we introduce two basic principles for information metamaterials: Shannon entropy on metamaterials to measure the information capacity quantitatively and digital convolution on metamaterials to manipulate the beam steering. Afterwards, two proof‐of‐concept imaging systems based on information metamaterials, i.e. programmable hologram and programmable imager, are presented, showing more powerful abilities than the traditional counterparts. Furthermore, we discuss the time‐modulated information metamaterial that enables efficient and accurate manipulations of spectral harmonic distributions and brings new physical phenomena such as frequency cloaking and velocity illusion. As a relevant application of time‐modulated information metamaterials, we propose a novel architecture of wireless communication, which simplifies the modern wireless communication system. Finally, the future trends of information metamaterials are predicted. Metamaterial ; Computer science ; Cloaking ; Transformation optics ; Electronic engineering ; Physics ; Optics ; Engineering Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: Carlos Echaide‐Górriz | Coralie Clément | Fernando Cacho‐Bailo | Carlos Téllez | Joaquı́n Coronas
Source: Journal of Materials Chemistry A (article, 2018-01-01)
Field: Chemistry — Inorganic Chemistry

New strategies based on microfluidics for the synthesis of metal–organic frameworks and their membranes The microfluidics approach allows not only the continuous production of metal–organic frameworks (MOFs) but also an accurate reaction parameter control in their synthesis. Microfluidics ; Metal-organic framework ; Membrane ; Nanotechnology ; Production (economics) ; Organic synthesis ; Biochemical engineering ; Process engineering ; Materials science ; Computer science ; Engineering ; Chemistry ; Organic chemistry ; Catalysis Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Supramolecular Chemistry and Complexes
Authors: Yu Nakashima | Takahiro Mori | Hitomi Nakamura | Takayoshi Awakawa | Shotaro Hoshino | Miki Senda | Toshiya Senda | Ikuro Abe
Source: Nature Communications (article, 2018-01-03)
Field: Chemistry — Inorganic Chemistry

Structure function and engineering of multifunctional non-heme iron dependent oxygenases in fungal meroterpenoid biosynthesis Abstract Non-heme iron and α-ketoglutarate (αKG) oxygenases catalyze remarkably diverse reactions using a single ferrous ion cofactor. A major challenge in studying this versatile family of enzymes is to understand their structure–function relationship. AusE from Aspergillus nidulans and PrhA from Penicillium brasilianum are two highly homologous Fe(II)/αKG oxygenases in fungal meroterpenoid biosynthetic pathways that use preaustinoid A1 as a common substrate to catalyze divergent rearrangement reactions to form the spiro-lactone in austinol and cycloheptadiene moiety in paraherquonin, respectively. Herein, we report the comparative structural study of AusE and PrhA, which led to the identification of three key active site residues that control their reactivity. Structure-guided mutagenesis of these residues results in successful interconversion of AusE and PrhA functions as well as generation of the PrhA double and triple mutants with expanded catalytic repertoire. Manipulation of the multifunctional Fe(II)/αKG oxygenases thus provides an excellent platform for the future development of biocatalysts. Oxygenase ; Mutagenesis ; Heme ; Cofactor ; Aspergillus nidulans ; Enzyme ; Biochemistry ; Chemistry ; Biosynthesis ; Stereochemistry ; Active site ; Moiety ; Protein engineering ; Biology ; Computational biology ; Mutant ; Gene Metal-Catalyzed Oxygenation Mechanisms ; Microbial Natural Products and Biosynthesis ; Plant biochemistry and biosynthesis
Authors: Michael Eickenberg | Georgios Exarchakis | Matthew Hirn | Stéphane Mallat | Louis Thiry
Source: The Journal of Chemical Physics (article, 2018-05-14)
Field: Materials Science — Materials Chemistry

Solid harmonic wavelet scattering for predictions of molecule properties We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory (DFT). Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which we compute invariant "solid harmonic scattering coefficients" that account for different types of interactions at different scales. Multilinear regressions of various physical properties of molecules are computed from these invariant coefficients. Numerical experiments show that these regressions have near state-of-the-art performance, even with relatively few training examples. Predictions over small sets of scattering coefficients can reach a DFT precision while being interpretable. Multilinear map ; Scattering ; Gaussian ; Density functional theory ; Invariant (physics) ; Statistical physics ; Harmonic ; Wavelet ; Molecule ; Mathematics ; Physics ; Computational physics ; Quantum mechanics ; Computer science ; Artificial intelligence Machine Learning in Materials Science ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Rachel Woods‐Robinson | Danny Broberg | Alireza Faghaninia | Anubhav Jain | Shyam Dwaraknath | Kristin A. Persson
Source: Chemistry of Materials (article, 2018-10-30)
Field: Materials Science — Materials Chemistry

Assessing High-Throughput Descriptors for Prediction of Transparent Conductors The growth of materials databases has yielded significant quantities of data to mine for new energy materials using high-throughput screening methodologies. One application of interest to energy and optoelectronics is the prediction of new high performing p-type transparent conductors (TCs). However, screening methods for such materials have never been validated over the breadth of computed materials properties. In this study, we compile an experimental data set of 74 bulk crystal structures corresponding to known state-of-the-art n-type and p-type TCs and compute a series of corresponding computational descriptor properties. Our goals are to (1) compare computational descriptors to experimentally demonstrated properties of real materials in the data set, (2) determine the ability of ground state, density functional theory (DFT)-based computational screening methodologies to identify these experimentally realized TCs, and (3) use this understanding to estimate reasonable screening cutoffs for four commonly used descriptors. First, stability calculations demonstrate that most materials in the data set have an energy above the convex hull (Ehull) of <100 meV/atom, and we also propose a Pourbaix analysis technique to estimate moisture stability. Second, we find a lenient cutoff for the DFT PBE band gap of 0.5 eV is sufficient to include a majority of the wide gap candidates and exclude narrow gap compounds. Next, the effective mass, m*, is found to correlate weakly to conductivity in the p-type materials as compared with n-type materials, which may motivate an increase in the m* cutoff as well. Lastly, we perform an uncertainty analysis and literature comparison for the branch point energy (BPE), a qualitative descriptor for dopability. We find the BPEs of most n-type materials to lie near the conduction band and those of most p-type materials to lie at midgap; this is a significant distinction, suggesting BPE to be a more definitive descriptor for n-type TC materials. By assessing the validity of this simple screening methodology via comparing experimental data to computational descriptors, we aim to motivate and strengthen future materials discovery efforts in the field of transparent conductors and beyond. Cutoff ; Stability (learning theory) ; CASTEP ; Convex hull ; Electrical conductor ; Density functional theory ; Set (abstract data type) ; Basis set ; Band gap ; Type (biology) ; Throughput ; Computer science ; Materials science ; Algorithm ; Mathematics ; Regular polygon ; Physics ; Chemistry ; Computational chemistry ; Machine learning ; Quantum mechanics ; Optoelectronics Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Transition Metal Oxide Nanomaterials
Authors: Puneet Mishra | Alison Nordon | Julius Tschannerl | Guoping Lian | Sally Redfern | Stephen Marshall
Source: Journal of Food Engineering (article, 2018-06-13)
Field: Chemistry — Analytical Chemistry

Near-infrared hyperspectral imaging for non-destructive classification of commercial tea products Isomap ; Hyperspectral imaging ; Support vector machine ; Artificial intelligence ; Pattern recognition (psychology) ; Computer science ; Principal component analysis ; Dimensionality reduction ; Nonlinear dimensionality reduction Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Identification and Quantification in Food
Authors: Mathias Jørgensen | Uffe F. Larsen | Karsten W. Jacobsen | Bjørk Hammer
Source: The Journal of Physical Chemistry A (article, 2018-01-09)
Field: Materials Science — Materials Chemistry

Exploration versus Exploitation in Global Atomistic Structure Optimization The ability to navigate vast energy landscapes of molecules, clusters, and solids is a necessity for discovering novel compounds in computational chemistry and materials science. For high-dimensional systems, it is only computationally feasible to search a small portion of the landscape, and hence, the search strategy is of critical importance. Introducing Bayesian optimization concepts in an evolutionary algorithm framework, we quantify the concepts of exploration and exploitation in global minimum searches. The method allows us to control the balance between probing unknown regions of the landscape (exploration) and investigating further regions of the landscape known to have low-energy structures (exploitation). The search for global minima structures proves significantly faster with the optimal balance for three test systems (molecular compounds) and to a lesser extent also for a crystalline surface reconstruction. In addition, global search behaviors are analyzed to provide reasonable grounds for an optimal balance for different problems. Maxima and minima ; Fitness landscape ; Energy landscape ; Computer science ; Bayesian optimization ; Global optimization ; Balance (ability) ; Mathematical optimization ; Algorithm ; Mathematics ; Artificial intelligence ; Chemistry ; Biology Machine Learning in Materials Science ; Protein Structure and Dynamics ; Computational Drug Discovery Methods