jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Raju Dash | Md. Chayan Ali | Nayan Dash | Md. Abul Kalam Azad | S. M. Zahid Hosen | Md. Abdul Hannan | Il Soo Moon
Source: International Journal of Molecular Sciences (article, 2019-12-11)
Field: Chemistry — Spectroscopy

Structural and Dynamic Characterizations Highlight the Deleterious Role of SULT1A1 R213H Polymorphism in Substrate Binding Sulfotransferase 1A1 (SULT1A1) is responsible for catalyzing various types of endogenous and exogenous compounds. Accumulating data indicates that the polymorphism rs9282861 (R213H) is responsible for inefficient enzymatic activity and associated with cancer progression. To characterize the detailed functional consequences of this mutation behind the loss-of-function of SULT1A1, the present study deployed molecular dynamics simulation to get insights into changes in the conformation and binding energy. The dynamics scenario of SULT1A1 in both wild and mutated types as well as with and without ligand showed that R213H induced local conformational changes, especially in the substrate-binding loop rather than impairing overall stability of the protein structure. The higher conformational changes were observed in the loop3 (residues, 235-263), turning loop conformation to A-helix and B-bridge, which ultimately disrupted the plasticity of the active site. This alteration reduced the binding site volume and hydrophobicity to decrease the binding affinity of the enzyme to substrates, which was highlighted by the MM-PBSA binding energy analysis. These findings highlight the key insights of structural consequences caused by R213H mutation, which would enrich the understanding regarding the role of SULT1A1 mutation in cancer development and also xenobiotics management to individuals in the different treatment stages. Molecular dynamics ; Binding site ; Enzyme ; Conformational change ; Biology ; Biophysics ; Mutation ; Ligand (biochemistry) ; Biochemistry ; Transition (genetics) ; Chemistry ; Stereochemistry ; Receptor ; Gene ; Computational chemistry Mass Spectrometry Techniques and Applications ; Enzyme Structure and Function ; Advanced Proteomics Techniques and Applications
Authors: Felix Ziegler | Johannes Teske | Iris Elser | Michael Dyballa | Wolfgang Frey | Hamzeh Kraus | Niels Hansen | Julia Rybka | Ulrich Tallarek | Michael R. Buchmeiser
Source: Journal of the American Chemical Society (article, 2019-11-07)
Field: Chemistry — Organic Chemistry

Olefin Metathesis in Confined Geometries: A Biomimetic Approach toward Selective Macrocyclization The synthesis of macrocycles is severely impeded by concomitant oligomer formation. Here, we present a biomimetic approach that utilizes spatial confinement to increase macrocyclization selectivity in the ring-closing metathesis of various dienes at elevated substrate concentration up to 25 mM using an olefin metathesis catalyst selectively immobilized inside ordered mesoporous silicas with defined pore diameters. By this approach, the ratio between macro(mono)cyclization (MMC) product and all undesired oligomerization products (O) resulting from acyclic diene metathesis polymerization was increased from 0.55, corresponding to 35% MMC product obtained with the homogeneous catalyst, up to 1.49, corresponding to 60% MMC product. A correlation between the MMC/O ratio and the substrate-to-pore-size ratio was successfully established. Modification of the inner pore surface with dimethoxydimethylsilane allowed fine-tuning the effective pore size and reversing surface polarity, which resulted in a further increase of the MMC/O ratio up to 2.2, corresponding to >68% MMC product. Molecular-level simulations in model pore geometries help to rationalize the complex interplay between spatial confinement, specific (substrate and product) interaction with the pore surface, and diffusive transport. These effects can be synergistically adjusted for optimum selectivity by suitable surface modification. Chemistry ; Selectivity ; Metathesis ; Mesoporous material ; Substrate (aquarium) ; Catalysis ; Propene ; Chemical engineering ; Polymerization ; Ring-opening metathesis polymerisation ; Oligomer ; Salt metathesis reaction ; Polymer chemistry ; Organic chemistry ; Polymer Synthetic Organic Chemistry Methods ; biodegradable polymer synthesis and properties ; Polymer Surface Interaction Studies
Authors: James T. Cahill | Olivia A. Graeve
Source: Journal of Materials Research and Technology (review, 2019-09-30)
Field: Materials Science — Materials Chemistry

Hexaborides: a review of structure, synthesis and processing Hexaboride compounds are a subset of borides with many interesting thermal, electrical, magnetic and physical properties. As such, interest has grown in this class of ceramics not only to understand their peculiar characteristics, but also to apply them to modern scientific and engineering problems. Hexaborides are currently used or show promise for a variety of applications such as electron emitters, thermoelectric materials, coatings, single-photon detectors and superconductors. A shared crystal structure amongst all hexaborides permits them to readily form solid solutions, allowing for fine-tuning of electrical, optical and thermal properties with mixed-metal compounds. Recent advances in characterization techniques have allowed researchers to gain new insights and renewed interest in some of the more exotic hexaboride behaviors such as surface conductivity in SmB6 or magnetic ordering in CeB6. Like many other non-oxide ceramics, borides present certain synthesis and processing challenges. This paper presents an overview of the structure, synthesis and processing of hexaboride compounds in an effort to guide researchers with the first step in pursuing these interesting and unique materials. Keywords: Hexaboride, Synthesis, Sintering, Processing, Ceramic Materials science ; Characterization (materials science) ; Nanotechnology ; Superconductivity ; Ceramic ; Engineering physics ; Thermoelectric effect ; Oxide ; Metallurgy ; Condensed matter physics ; Engineering Boron and Carbon Nanomaterials Research ; Rare-earth and actinide compounds ; Advanced materials and composites
Authors: Yang Liu | Yan‐Cong Chen | Jiang Liu | Wen‐Bin Chen | Guo‐Zhang Huang | Si‐Guo Wu | Jin Wang | Jun‐Liang Liu | Ming‐Liang Tong
Source: Inorganic Chemistry (article, 2019-12-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Cyanometallate-Bridged Didysprosium Single-Molecule Magnets Constructed with Single-Ion Magnet Building Block The combination of magnetic interaction with high magnetic anisotropy provides a promising way for modulating/fine-tuning molecular magnetic behaviors. Here, we show the building block approach for the synthesis of a family of dilanthanide single-molecule magnets (SMMs) bridged with a cyanometallate starting from a monolanthanide SMM. Contingent on the central para-/diamagnetic [M(CN)<sub>6</sub>]<sup>3-</sup> (M = Fe, Co) integrated between two highly anisotropic pentagonal-bipyramid Dy(III) subunits, the remanence of magnetization is OFF/ON below 15 K and they respectively display a record reversal barrier of 659 K among d-f SMMs and 975 K among cyano-bridged SMMs. Chemistry ; Diamagnetism ; Magnet ; Single-molecule magnet ; Remanence ; Magnetization ; Block (permutation group theory) ; Anisotropy ; Crystallography ; Magnetic anisotropy ; Pentagonal bipyramidal molecular geometry ; Molecule ; Ion ; Magnetic field ; Crystal structure ; Physics ; Geometry ; Organic chemistry ; Optics Magnetism in coordination complexes ; Lanthanide and Transition Metal Complexes ; Organic and Molecular Conductors Research
Authors: Rui Zhong | Zeyuan Wei | Wei Zhang | Shun Liu | Qiang Liu
Source: Chem (article, 2019-04-11)
Field: Chemistry — Inorganic Chemistry

A Practical and Stereoselective In Situ NHC-Cobalt Catalytic System for Hydrogenation of Ketones and Aldehydes Stereoselectivity ; In situ ; Cobalt ; Catalysis ; Chemistry ; Organic chemistry ; Combinatorial chemistry Asymmetric Hydrogenation and Catalysis ; Carbon dioxide utilization in catalysis ; Nanomaterials for catalytic reactions
Authors: Sagana Thamboo | Adrian Najer | Andrea Belluati | Claudio von Planta | Dalin Wu | Ioana Craciun | Wolfgang Meier | Cornelia G. Palivan
Source: Advanced Functional Materials (article, 2019-08-09)
Field: Materials Science — Biomaterials

Mimicking Cellular Signaling Pathways within Synthetic Multicompartment Vesicles with Triggered Enzyme Activity and Induced Ion Channel Recruitment Abstract Subcellular compartmentalization of cells, a defining characteristic of eukaryotes, is fundamental for the fine tuning of internal processes and the responding to external stimuli. Reproducing and controlling such compartmentalized hierarchical organization, responsiveness, and communication is important toward understanding biological systems and applying them to smart materials. Herein, a cellular signal transduction strategy (triggered release from subcompartments) is leveraged to develop responsive, purely artificial, polymeric multicompartment assemblies. Incorporation of responsive nanoparticles—loaded with enzymatic substrate or ion channels—as subcompartments inside micrometer‐sized polymeric vesicles (polymersomes) allowed to conduct bioinspired signaling cascades. Response of these subcompartments to an externally added stimulus is achieved and studied by using confocal laser scanning microscopy (CLSM) coupled with in situ fluorescence correlation spectroscopy (FCS). Signal triggered activity of an enzymatic reaction is demonstrated in multicompartments through recombination of compartmentalized substrate and enzyme. In parallel, a two‐step signaling cascade is achieved by triggering the recruitment of ion channels from inner subcompartments to the vesicles' membrane, inducing ion permeability, mimicking endosome‐mediated insertion of internally stored channels. This design shows remarkable versatility, robustness, and controllability, demonstrating that multicompartment polymer‐based assemblies offer an ideal scaffold for the development of complex cell‐inspired responsive systems for applications in biosensing, catalysis, and medicine. Polymersome ; Ion channel ; Biophysics ; Materials science ; Nanotechnology ; Vesicle ; Artificial cell ; Compartmentalization (fire protection) ; Signal transduction ; Membrane ; Cell biology ; Chemistry ; Enzyme ; Biochemistry ; Biology ; Polymer ; Amphiphile Supramolecular Self-Assembly in Materials ; Advanced Polymer Synthesis and Characterization ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Yang Huang | Changyou Yu | Weiguang Chen | Yuhuai Liu | Chong Li | Chunyao Niu | Fei Wang | Yu Jia
Source: Journal of Materials Chemistry C (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Band gap and band alignment prediction of nitride-based semiconductors using machine learning Machine learning has been utilized to accurately predict band gap and band alignment of wurtzite nitrides in a large design space. Band gap ; Semiconductor ; Wurtzite crystal structure ; Wide-bandgap semiconductor ; Out-of-band management ; Electronic band structure Machine Learning in Materials Science ; Boron and Carbon Nanomaterials Research ; Ga2O3 and related materials
Authors: Stuke, A. | Todorović, M. | Rupp, M. | Kunkel, C. | Ghosh, K.
Source: MPG.PuRe (Max Planck Society) (article, 2019-05-28)
Field: Materials Science — Materials Chemistry

Chemical diversity in molecular orbital energy predictions with kernel ridge regression Instant machine learning predictions of molecular properties are desirable for materials design, but the predictive power of the methodology is mainly tested on well-known benchmark datasets. Here, we investigate the performance of machine learning with kernel ridge regression (KRR) for the prediction of molecular orbital energies on three large datasets: the standard QM9 small organic molecules set, amino acid and dipeptide conformers, and organic crystal-forming molecules extracted from the Cambridge Structural Database. We focus on the prediction of highest occupied molecular orbital (HOMO) energies, computed at the density-functional level of theory. Two different representations that encode the molecular structure are compared: the Coulomb matrix (CM) and the many-body tensor representation (MBTR). We find that KRR performance depends significantly on the chemistry of the underlying dataset and that the MBTR is superior to the CM, predicting HOMO energies with a mean absolute error as low as 0.09 eV. To demonstrate the power of our machine learning method, we apply our model to structures of 10k previously unseen molecules. We gain instant energy predictions that allow us to identify interesting molecules for future applications. Kernel (algebra) ; Benchmark (surveying) ; Artificial intelligence ; Molecular orbital ; Computer science ; Molecule ; Statistical physics ; HOMO/LUMO ; Machine learning ; Physics ; Mathematics ; Quantum mechanics ; Combinatorics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Crystallography and molecular interactions
Authors: Junzhu Li | Mingguang Chen | Chenhui Zhang | Haocong Dong | Weiyi Lin | Pingping Zhuang | Yan Wen | Bo Tian | Weiwei Cai | Xixiang Zhang
Source: Advanced Materials (article, 2019-07-02)
Field: Materials Science — Materials Chemistry

Fractal‐Theory‐Based Control of the Shape and Quality of CVD‐Grown 2D Materials The precise control of the shape and quality of 2D materials during chemical vapor deposition (CVD) processes remains a challenging task, due to a lack of understanding of their underlying growth mechanisms. The existence of a fractal-growth-based mechanism in the CVD synthesis of several 2D materials is revealed, to which a modified traditional fractal theory is applied in order to build a 2D diffusion-limited aggregation (2D-DLA) model based on an atomic-scale growth mechanism. The strength of this model is validated by the perfect correlation between theoretically simulated data, predicted by 2D-DLA, and experimental results obtained from the CVD synthesis of graphene, hexagonal boron nitride, and transition metal dichalcogenides. By applying the 2D-DLA model, it is also discovered that the single-domain net growth rate (SD-NGR) plays a crucial factor in governing the shape and quality of 2D-material crystals. By carefully tuning SD-NGR, various fractal-morphology high-quality single-crystal 2D materials are synthesized, achieving, for the first time, the precise control of 2D-material CVD growth. This work lays the theoretical foundation for the precise adjustment of the morphologies and physical properties of 2D materials, which is essential to the use of fractal-shaped nanomaterials for the fabrication of new-generation neural-network nanodevices. Materials science ; Fractal ; Quality (philosophy) ; Nanotechnology ; Engineering physics ; Mathematics ; Mathematical analysis ; Engineering ; Quantum mechanics ; Physics Graphene research and applications ; Thermal properties of materials ; Composite Material Mechanics
Authors: Chuanpin Chen | Wenfang Liu | Sanping Tian | Tingting Hong
Source: Sensors (review, 2019-04-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Novel Surface-Enhanced Raman Spectroscopy Techniques for DNA, Protein and Drug Detection Surface-enhanced Raman spectroscopy (SERS) is a vibrational spectroscopic technique in which the Raman scattering signal strength of molecules, absorbed by rough metals or the surface of nanoparticles, experiences an exponential growth (10³-10⁶ times and even 10<sup>14</sup>-10<sup>15</sup> times) because of electromagnetic or chemical enhancements. Nowadays, SERS has attracted tremendous attention in the field of analytical chemistry due to its specific advantages, including high selectivity, rich informative spectral properties, nondestructive testing, and the prominent multiplexing capabilities of Raman spectroscopy. In this review, we present the applications of state-of-the-art SERS for the detection of DNA, proteins and drugs. Moreover, we focus on highlighting the merits and mechanisms of achieving enhanced SERS signals for food safety and clinical treatment. The machine learning techniques, combined with SERS detection, are also indicated herein. This review concludes with recommendations for future studies on the development of SERS. Raman spectroscopy ; Raman scattering ; Surface-enhanced Raman spectroscopy ; Nanotechnology ; Materials science ; Spectroscopy ; Nanoparticle ; Multiplexing ; Chemistry ; Computer science ; Optics ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Biosensors and Analytical Detection
Authors: Mahboubeh Pishnamazi | Hamza Y. Ismail | Saeed Shirazian | Javed Iqbal | Gavin Walker | Maurice N. Collins
Source: Cellulose (article, 2019-05-25)
Field: Chemistry — Analytical Chemistry

Application of lignin in controlled release: development of predictive model based on artificial neural network for API release Dissolution ; Granulation ; Tableting ; Materials science ; Lignin ; Artificial neural network ; Compaction ; Kriging ; Paeoniflorin ; Excipient ; Chemical engineering ; Biological system ; Chromatography ; Composite material ; Computer science ; Machine learning ; Chemistry ; High-performance liquid chromatography ; Organic chemistry ; Engineering Chromatography in Natural Products ; Lignin and Wood Chemistry ; Polysaccharides Composition and Applications
Authors: Ana S. C. Silva | Robbin Bouwmeester | Lennart Martens | Sven Degroeve
Source: Bioinformatics (article, 2019-05-02)
Field: Chemistry — Spectroscopy

Accurate peptide fragmentation predictions allow data driven approaches to replace and improve upon proteomics search engine scoring functions Supplementary data are available at Bioinformatics online. Computer science ; Search engine ; Data mining ; Similarity (geometry) ; Machine learning ; Source code ; Fragmentation (computing) ; Software ; Mascot ; Artificial intelligence ; Information retrieval Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Machine Learning in Bioinformatics
Authors: Shreya Saha | Nahid Chaudhary | Honey Mittal | Govind Gupta | Manika Khanuja
Source: International nano letters. (article, 2019-03-02)
Field: Materials Science — Polymers and Plastics

Inorganic–organic nanohybrid of MoS2-PANI for advanced photocatalytic application In this work, the fabrication of MoS2-Polyaniline (PANI) nanocomposites, by in situ polymerization, has been described and its application as a photocatalyst for the degradation of organic pollutants such as methylene blue (MB) and 4-chlorophenol (4-CP), has been reported. The disadvantages of MoS2 such as poor electronic conductivity and agglomeration between the nanosheets, was overcome by intercalating 2D MoS2 layers with 1D conducting polymer, Polyaniline (PANI). The composite material was characterised by SEM, TEM, BET, XRD, FTIR, UV–Vis spectroscopy and XPS, indicating proper intercalation between MoS2 nanosheets and PANI. Consequently, the synthesized composites were used for the degradation of MB and 4-CP, followed by kinetic investigations to determine the rate kinetics. The photoactivity of the nanocomposite is explained by the transfer of photogenerated electrons from PANI to the CB of MoS2, thus preventing the direct recombination of electrons and holes. Hence, a positive synergistic effect between MoS2 and PANI resulted in efficient photocatalytic degradation of organic dyes like MB. Polyaniline ; Materials science ; Nanocomposite ; Photocatalysis ; X-ray photoelectron spectroscopy ; Chemical engineering ; Fourier transform infrared spectroscopy ; Polymerization ; Methylene blue ; Intercalation (chemistry) ; Conductive polymer ; Degradation (telecommunications) ; Nanochemistry ; Polymer ; Nanotechnology ; Composite material ; Inorganic chemistry ; Catalysis ; Organic chemistry ; Chemistry Conducting polymers and applications ; 2D Materials and Applications ; Advanced Photocatalysis Techniques
Authors: Yixuan Wang | Hongjun Li | Lihua Guo | Qi Jiang | Feng Liu
Source: RSC Advances (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

A cobalt-doped iron oxide nanozyme as a highly active peroxidase for renal tumor catalytic therapy The Fe<sub>3</sub>O<sub>4</sub> nanozyme, the first reported nanozyme with intrinsic peroxidase-like activity, has been successfully employed for various diagnostic applications. However, only a few studies have been reported on the therapeutic applications of the Fe<sub>3</sub>O<sub>4</sub> nanozyme partly due to its low affinity to the substrate H<sub>2</sub>O<sub>2</sub>. Herein, we report a new strategy for improving the peroxidase-like activity and affinity of the Fe<sub>3</sub>O<sub>4</sub> nanozyme to H<sub>2</sub>O<sub>2</sub> to generate reactive oxygen species (ROS) for kidney tumor catalytic therapy. We showed that cobalt-doped Fe<sub>3</sub>O<sub>4</sub> (Co@Fe<sub>3</sub>O<sub>4</sub>) nanozymes possessed stronger peroxidase activity and a 100-fold higher affinity to H<sub>2</sub>O<sub>2</sub> than the Fe<sub>3</sub>O<sub>4</sub> nanozymes. The lysosome localization properties of Co@Fe<sub>3</sub>O<sub>4</sub> enable Co@Fe<sub>3</sub>O<sub>4</sub> to catalyze the decomposition of H<sub>2</sub>O<sub>2</sub> at ultralow doses for the generation of ROS bursts to effectively kill human renal tumor cells both <i>in vitro</i> and <i>in vivo</i>. Moreover, our study provides the first evidence that the Co@Fe<sub>3</sub>O<sub>4</sub> nanozyme is a powerful nanozyme for the generation of ROS bursts upon the addition of H<sub>2</sub>O<sub>2</sub> at ultralow doses, presenting a potential novel avenue for tumor nanozyme catalytic therapy. Peroxidase ; Reactive oxygen species ; Chemistry ; Catalysis ; In vitro ; Cobalt ; Substrate (aquarium) ; In vivo ; Cancer research ; Combinatorial chemistry ; Biophysics ; Enzyme ; Biochemistry ; Medicine ; Inorganic chemistry ; Biology Advanced Nanomaterials in Catalysis ; Nanoplatforms for cancer theranostics ; Nanocluster Synthesis and Applications