jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nan Nan | Jie Wang | Yuejie Shi | Yangwen Qian | Long Jiang | Shuangzhan Huang | Yutong Liu | Ying Wu | Liu B | Zheng‐Yi Xu
Source: Plant Biotechnology Journal (article, 2019-06-04)
Field: Materials Science — Materials Chemistry

Rice plastidial <scp>NAD</scp>‐dependent malate dehydrogenase 1 negatively regulates salt stress response by reducing the vitamin B6 content Summary Salinity is an important environmental factor that adversely impacts crop growth and productivity. Malate dehydrogenases ( MDH s) catalyse the reversible interconversion of malate and oxaloacetate using NAD (H)/ NADP (H) as a cofactor and regulate plant development and abiotic stress tolerance. Vitamin B6 functions as an essential cofactor in enzymatic reactions involved in numerous cellular processes. However, the role of plastidial MDH in rice ( Oryza sativa ) in salt stress response by altering vitamin B6 content remains unknown. In this study, we identified a new loss‐of‐function osmdh1 mutant displaying salt stress‐tolerant phenotype. The Os MDH 1 was expressed in different tissues of rice plants including leaf, leaf sheath, panicle, glume, bud, root and stem and was induced in the presence of NaCl. Transient expression of Os MDH 1‐ GFP in rice protoplasts showed that Os MDH 1 localizes to chloroplast. Transgenic rice plants overexpressing Os MDH 1 ( Os MDH 1 OX ) displayed a salt stress‐sensitive phenotype. Liquid chromatography–mass spectrometry ( LC ‐ MS ) metabolic profiling revealed that the amount of pyridoxine was significantly reduced in Os MDH 1 OX lines compared with the NIP plants. Moreover, the pyridoxine content was higher in the osmdh1 mutant and lower in Os MDH 1 OX plants than in the NIP plants under the salt stress, indicating that Os MDH 1 negatively regulates salt stress‐induced pyridoxine accumulation. Furthermore, genome‐wide RNA ‐sequencing ( RNA ‐seq) analysis indicated that ectopic expression of Os MDH 1 altered the expression level of genes encoding key enzymes of the vitamin B6 biosynthesis pathway, possibly reducing the level of pyridoxine. Together, our results establish a novel, negative regulatory role of Os MDH 1 in salt stress tolerance by affecting vitamin B6 content of rice tissues. Biology ; Biochemistry ; Oryza sativa ; Mutant ; Malate dehydrogenase ; Alcohol dehydrogenase ; NAD+ kinase ; Abiotic stress ; Wild type ; Enzyme ; Gene Enzyme Structure and Function ; Photosynthetic Processes and Mechanisms ; GABA and Rice Research
Authors: John Bradshaw | Brooks Paige | Matt J. Kusner | Marwin Segler | José Miguel Hernández-Lobato
Source: PolyPublie (École Polytechnique de Montréal) (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

A Model to Search for Synthesizable Molecules Deep generative models are able to suggest new organic molecules by generating strings, trees, and graphs representing their structure. While such models allow one to generate molecules with desirable properties, they give no guarantees that the molecules can actually be synthesized in practice. We propose a new molecule generation model, mirroring a more realistic real-world process, where (a) reactants are selected, and (b) combined to form more complex molecules. More specifically, our generative model proposes a bag of initial reactants (selected from a pool of commercially-available molecules) and uses a reaction model to predict how they react together to generate new molecules. We first show that the model can generate diverse, valid and unique molecules due to the useful inductive biases of modeling reactions. Furthermore, our model allows chemists to interrogate not only the properties of the generated molecules but also the feasibility of the synthesis routes. We conclude by using our model to solve retrosynthesis problems, predicting a set of reactants that can produce a target product. Retrosynthetic analysis ; Computer science ; Mirroring ; Molecule ; Set (abstract data type) ; Generative model ; Generative grammar ; Process (computing) ; Theoretical computer science ; Artificial intelligence ; Chemistry ; Programming language ; Stereochemistry Machine Learning in Materials Science ; Software Engineering Research ; Computational Drug Discovery Methods
Authors: Hongmei Tang | Wenyao Li | Haishun Jiang | Runjia Lin | Zhe Wang | Jianghong Wu | Guanjie He | Paul R. Shearing | Dan J. L. Brett
Source: Nanomaterials (article, 2019-01-18)
Field: Materials Science — Materials Chemistry

ZIF-8-Derived Hollow Carbon for Efficient Adsorption of Antibiotics The harmful nature of high concentrations of antibiotics to humans and animals requires the urgent development of novel materials and techniques for their absorption. In this work, CTAB (Cetyltrimethyl Ammonium Bromide)-assisted synthesis of ZIF-8 (zeolitic imidazolate framework)-derived hollow carbon (ZHC) was designed, prepared, and used as a high-performance adsorbent, and further evaluated by Langmuir and Freundlich isothermal adsorption experiments, dynamic analysis, as well as theoretical calculation. The maximum capacities of ZHC for adsorbing tetracycline (TC), norfloxacin (NFO), and levofloxacin (OFO) are 267.3, 125.6, and 227.8 mg g<sup>-1</sup>, respectively, which delivers superior adsorptive performance when compared to widely studied inorganic adsorbates. The design concept of ZIF-8-derived hollow carbon material provides guidance and insights for the efficient adsorbent of environmental antibiotics. Adsorption ; Carbon fibers ; Antibiotics ; Materials science ; Chemical engineering ; Environmental chemistry ; Chemistry ; Organic chemistry ; Composite material ; Engineering ; Composite number Covalent Organic Framework Applications ; Adsorption and biosorption for pollutant removal ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Qingliang Cui | Gaojie Jiao | Jiyong Zheng | Tongtong Wang | Gao‐Lin Wu | Gaoliang Li
Source: RSC Advances (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Synthesis of a novel magnetic <i>Caragana korshinskii</i> biochar/Mg–Al layered double hydroxide composite and its strong adsorption of phosphate in aqueous solutions Phosphate pollution of aquatic ecosystems is of great concern and requires the development of high-performance materials for effective pollution treatment. To realize efficient phosphate removal from aqueous solution, an easily separable magnetic (Fe<sub>3</sub>O<sub>4</sub>) <i>Caragana korshinskii</i> biochar/Mg-Al layered double hydroxide composite (denoted as FCB/MAC) was synthesized <i>via</i> two-step electro-assisted modification for the first time. Subsequently, the physical and chemical properties of FCB/MAC were characterized. Furthermore, the sorption mechanism for phosphate removal was investigated in detail. The results indicated that Fe<sub>3</sub>O<sub>4</sub> and the Mg-Al layered double hydroxide were successfully embedded in the biochar matrix. Moreover, FCB/MAC exhibited a high phosphate adsorption capacity and excellent magnetic properties for easy recovery. The maximum phosphate sorption capacity of FCB/MAC was 252.88 mg g<sup>-1</sup>, which is much higher than the capacities of most magnetic phosphate adsorbents. In addition, the adsorption kinetics and isotherms indicated that phosphate adsorption by FCB/MAC was controlled by the pseudo-second-order kinetic model and the Langmuir-Freundlich isotherm model. The phosphate adsorption mechanism involves anion exchange, electrostatic attraction, and ligand exchange. After five adsorption-desorption cycles, the phosphate adsorption capacity of FCB/MAC was 25.71 mg g<sup>-1</sup> with 51.43% removal efficiency and high recyclability. Thus, the composite prepared in this study is a promising adsorbent for phosphate removal from aqueous solution, and this work provides an excellent reference for constructing novel biochar-based phosphate adsorbents. Adsorption ; Biochar ; Phosphate ; Composite number ; Aqueous solution ; Hydroxide ; Chemistry ; Inorganic chemistry ; Layered double hydroxides ; Nuclear chemistry ; Materials science ; Organic chemistry ; Composite material ; Pyrolysis Layered Double Hydroxides Synthesis and Applications ; Phosphorus and nutrient management ; Adsorption and biosorption for pollutant removal
Authors: Michael Green | Anh Thi Van Tran | Russell Smedley | Adam Roach | James B. Murowchick | Xiaobo Chen
Source: Nano Materials Science (article, 2019-02-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Microwave absorption of magnesium/hydrogen-treated titanium dioxide nanoparticles Interactions between materials and electromagnetic irradiations in the microwave frequency are critical for many civil and military applications, such as radar detection, communications, information processing and transport et al. Dipole rotations or magnetic domain resonance are the mainly traditional mechanisms for microwave absorption. The recent finding of the excellent microwave absorption from hydrogenated TiO2 nanoparticles provides us an alternative approach for achieving such absorption, by manipulating the structural defects inside nanoparticles through hydrogenation. In this study, we demonstrate that the microwave absorption can be not only achieved but fine-tuned with TiO2 nanoparticles thermally treated in a Mg/H2 environment. Their position and efficiency can be effectively controlled by the treating temperature. Specifically, the microwave absorption position shifts to the lower frequency region as the treating temperature increases, and there seems to exist an optimal treating temperature to obtain the maximum efficiency, as the absorbing efficiency first increases, and then decreases, with the increase in treatment temperature. Therefore, this study enriches our knowledge and understanding microwave absorption from TiO2-based nanomaterials which may inspire new ideas on other systems to enhance their performance as well. Microwave ; Materials science ; Absorption (acoustics) ; Nanoparticle ; Nanomaterials ; Nanotechnology ; Titanium dioxide ; Optoelectronics ; Telecommunications ; Computer science ; Composite material Electromagnetic wave absorption materials ; Nanomaterials for catalytic reactions ; Magnetic Properties and Synthesis of Ferrites
Authors: Congwen Duan | Yizheng Cao | Lianxi Hu | Dong Fu | Jinlong Ma | Jeffrey P. Youngblood
Source: Journal of Hazardous Materials (article, 2019-03-15)
Field: Materials Science — Materials Chemistry

An efficient mechanochemical synthesis of alpha-aluminum hydride: Synergistic effect of TiF3 on the crystallization rate and selective formation of alpha-aluminum hydride polymorph Dehydrogenation ; Hydrogen storage ; Hydrogen ; Composite number ; Crystallization ; Hydride ; Materials science ; Gravimetric analysis ; Aluminium ; Desorption ; Chemical engineering ; Chemistry ; Inorganic chemistry ; Nuclear chemistry ; Catalysis ; Physical chemistry ; Metallurgy ; Organic chemistry ; Composite material ; Adsorption Hydrogen Storage and Materials ; Ammonia Synthesis and Nitrogen Reduction ; Hybrid Renewable Energy Systems
Authors: Muhammad Ahsan Iqbal | Michele Fedel
Source: Coatings (article, 2019-01-07)
Field: Materials Science — Materials Chemistry

Effect of Synthesis Conditions on the Controlled Growth of MgAl–LDH Corrosion Resistance Film: Structure and Corrosion Resistance Properties In this study, a series of MgAl–layered double hydroxide (LDH) thin films were synthesized by a single step hydrothermal process at different synthetic conditions on AA6082, and the combined effect of reaction temperatures and crystallization times on in situ growth MgAl–LDH structural geometry, growth rate, and more importantly on the corresponding corrosive resistance properties are briefly discussed. The synthesis of LDH was performed at reaction temperatures of 40, 60, 80, and 100 °C, while the treatment time was varied at 12, 18, and 24 h. The as-prepared synthetic coatings were characterized by scanning electron microscopy (SEM), energy dispersion spectroscopy (EDS), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR), while the corresponding corrosion protection efficiency of the developed coating was studied through potentiodynamic polarization studies and electrochemical impedance spectra. The findings demonstrated that extended crystallization time and reaction temperature impart a significant effect on the oriented growth of layered double hydroxide, the surface morphology, and on the film thickness, which had a remarkable influence on the LDH corrosion resistance ability. The LDH coated specimen developed at 100 °C for 18 h reaction time showed a more compact and dense structure compared to the traditional platelet structure obtained at 80 °C for 24 h crystallization time, and interestingly that compact structure exhibited the lowest corrosion current density, up to five orders of magnitude lower than that of bare AA6082. Corrosion ; Materials science ; Scanning electron microscope ; Dielectric spectroscopy ; Crystallization ; Hydroxide ; Fourier transform infrared spectroscopy ; Chemical engineering ; Coating ; Polarization (electrochemistry) ; Electrochemistry ; Metallurgy ; Composite material ; Chemistry Layered Double Hydroxides Synthesis and Applications ; Magnesium Oxide Properties and Applications ; Magnesium Alloys: Properties and Applications
Authors: Yue Tang | Idir Benaissa | Mathieu Huynh | Laure Vendier | Noël Lugan | Stéphanie Bastin | Philippe Belmont | Vincent César | Véronique Michelet
Source: Angewandte Chemie International Edition (article, 2019-04-08)
Field: Chemistry — Organic Chemistry

An Original L‐shape, Tunable N‐Heterocyclic Carbene Platform for Efficient Gold(I) Catalysis The synthesis and characterization of original NHC ligands based on an imidazo[1,5-a]pyridin-3-ylidene (IPy) scaffold functionalized with a flanking barbituric heterocycle is described as well as their use as tunable ligands for efficient gold-catalyzed C-N, C-O, and C-C bond formations. High activity, regio-, chemo-, and stereoselectivities are obtained for hydroelementation and domino processes, underlining the excellent performance (TONs and TOFs) of these IPy-based ligands in gold catalysis. The gold-catalyzed domino reactions of 1,6-enynes give rise to functionalized heterocycles in excellent isolated yields under mild conditions. The efficiency of the NHC gold 5<sup>Me</sup> complex is remarkable and mostly arises from a combination of steric protection and stabilization of the cationic Au<sup>I</sup> active species by ligand 1<sup>Me</sup> . Carbene ; Steric effects ; Catalysis ; Chemistry ; Domino ; Cationic polymerization ; Ligand (biochemistry) ; Combinatorial chemistry ; Stereochemistry ; Medicinal chemistry ; Polymer chemistry ; Organic chemistry Catalytic Alkyne Reactions ; Catalytic Cross-Coupling Reactions ; Catalytic C–H Functionalization Methods
Authors: Lei Chen | Shuo Wang | Qianqian Yu | Paul D. Topham | Changzhong Chen | Linge Wang
Source: Soft Matter (review, 2019-01-01)
Field: Materials Science — Biomaterials

A comprehensive review of electrospinning block copolymers Electrospinning provides a versatile and cost-effective route for the generation of continuous nanofibres with high surface area-to-volume ratio from various polymers. In parallel, block copolymers (BCPs) are promising candidates for many diverse applications, where nanoscale operation is exploited, owing to their intrinsic self-assembling behaviour at these length scales. Judicious combination of BCPs (with their ability to make nanosized domains at equilibrium) and electrospinning (with its ability to create nano- and microsized fibres and particles) allows one to create BCPs with high surface area-to-volume ratio to deliver higher efficiency or efficacy in their given application. Here, we give a comprehensive overview of the wide range of reports on BCP electrospinning with focus placed on the use of molecular design alongside control over specific electrospinning type and post-treatment methodologies to control the properties of the resultant fibrous materials. Particular attention is paid to the applications of these materials, most notably, their use as biomaterials, separation membranes, sensors, and electronic materials. Electrospinning ; Copolymer ; Block (permutation group theory) ; Polymer science ; Materials science ; Polymer chemistry ; Nanotechnology ; Polymer ; Composite material ; Mathematics Electrospun Nanofibers in Biomedical Applications ; Fuel Cells and Related Materials ; Conducting polymers and applications
Authors: S Saxena | Tuhin Suvra Khan | Fatima Jalid | Manojkumar Ramteke | M. Ali Haider
Source: Journal of Materials Chemistry A (article, 2019-09-13)
Field: Materials Science — Materials Chemistry

<i>In silico</i>high throughput screening of bimetallic and single atom alloys using machine learning and<i>ab initio</i>microkinetic modelling The advent of machine learning (ML) techniques in solving problems related to materials science and chemical engineering is driving expectations to give faster predictions of material properties. Bimetallic strip ; Ab initio ; Throughput ; Atom (system on chip) ; Ab initio quantum chemistry methods ; Computer science ; Machine learning ; Materials science ; Computational science ; Artificial intelligence ; Nanotechnology ; Chemistry ; Parallel computing ; Metallurgy ; Molecule Machine Learning in Materials Science ; Advanced Materials Characterization Techniques ; Fuel Cells and Related Materials
Authors: James Nelson | Stefano Sanvito
Source: Physical Review Materials (article, 2019-10-10)
Field: Materials Science — Materials Chemistry

Predicting the Curie temperature of ferromagnets using machine learning The magnetic properties of a material are determined by a subtle balance between the various interactions at play, a fact that makes the design of new magnets a daunting task. High-throughput electronic structure theory may help to explore the vast chemical space available and offers a design tool to the experimental synthesis. This method efficiently predicts the elementary magnetic properties of a compound and its thermodynamical stability, but it is blind to information concerning the magnetic critical temperature. Here we introduce a range of machine-learning models to predict the Curie temperature, $T_\mathrm{C}$, of ferromagnets. The models are constructed by using experimental data for about 2,500 known magnets and consider the chemical composition of a compound as the only feature determining $T_\mathrm{C}$. Thus, we are able to establish a one-to-one relation between the chemical composition and the critical temperature. We show that the best model can predict $T_\mathrm{C}$'s with an accuracy of about 50K. Most importantly our model is able to extrapolate the predictions to regions of the chemical space, where only a little fraction of the data was considered for training. This is demonstrated by tracing the $T_\mathrm{C}$ of binary intermetallic alloys along their composition space and for the Al-Co-Fe ternary system. Curie temperature ; Ternary operation ; Intermetallic ; Ferromagnetism ; Magnet ; Experimental data ; Space (punctuation) ; Parameter space Machine Learning in Materials Science ; Advanced Physical and Chemical Molecular Interactions ; X-ray Diffraction in Crystallography
Authors: Nan Qu | Yong Liu | Mingqing Liao | Zhonghong Lai | Fei Zhou | Puchang Cui | Tianyi Han | Danni Yang | Jingchuan Zhu
Source: Ceramics International (article, 2019-06-11)
Field: Materials Science — Materials Chemistry

Ultra-high temperature ceramics melting temperature prediction via machine learning Melting temperature ; Materials science ; Ceramic ; Artificial neural network ; Melting point ; Thermodynamics ; Machine learning ; Generality ; Work (physics) ; Artificial intelligence ; Computer science ; Metallurgy ; Composite material ; Physics Machine Learning in Materials Science ; Advanced materials and composites ; Metallurgical Processes and Thermodynamics
Authors: Mingjian Wen | Ellad B. Tadmor
Source: Physical review. B./Physical review. B (article, 2019-11-18)
Field: Materials Science — Materials Chemistry

Hybrid neural network potential for multilayer graphene Monolayer and multilayer graphene are promising materials for applications such as electronic devices, sensors, energy generation and storage, and medicine. In order to perform large-scale atomistic simulations of the mechanical and thermal behavior of graphene-based devices, accurate interatomic potentials are required. Here, we present an interatomic potential for multilayer graphene structures referred to as ``$\mathrm{hNN}\text{\ensuremath{-}}{\mathrm{Gr}}_{x}$.'' This hybrid potential employs a neural network to describe short-range interactions and a theoretically motivated analytical term to model long-range dispersion. The potential is trained against a large dataset of monolayer graphene, bilayer graphene, and graphite configurations obtained from ab initio total-energy calculations based on density functional theory (DFT). The potential provides accurate energy and forces for both intralayer and interlayer interactions, correctly reproducing DFT results for structural, energetic, and elastic properties such as the equilibrium layer spacing, interlayer binding energy, elastic moduli, and phonon dispersions to which it was not fit. The potential is used to study the effect of vacancies on thermal conductivity in monolayer graphene and interlayer friction in bilayer graphene. The potential is available through the openkim interatomic potential repository at https://openkim.org. Graphene ; Materials science ; Interatomic potential ; Phonon ; Monolayer ; Bilayer graphene ; Density functional theory ; Graphite ; Thermal conductivity ; Molecular dynamics ; Nanotechnology ; Potential energy ; Chemical physics ; Condensed matter physics ; Computational chemistry ; Composite material ; Chemistry ; Physics ; Atomic physics Graphene research and applications ; Thermal properties of materials ; Machine Learning in Materials Science
Authors: Simon Kern | Lukas Wander | Klas Meyer | Svetlana Guhl | Anwesh Reddy Gottu Mukkula | Manuel Holtkamp | Malte Salge | Christoph Fleischer | N. Weber | Rudibert King | Sebastian Engell | Andrea Paul | Manuel Pereira Remelhe | Michael Maiwald
Source: Analytical and Bioanalytical Chemistry (article, 2019-03-23)
Field: Chemistry — Spectroscopy

Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance. Graphical abstract. Process engineering ; Spectrometer ; Automation ; Modular design ; Quality assurance ; Computer science ; Flexibility (engineering) ; Biochemical engineering ; Environmental science ; Engineering ; Mechanical engineering ; Physics ; Mathematics Analytical Chemistry and Chromatography ; Innovative Microfluidic and Catalytic Techniques Innovation ; Spectroscopy and Chemometric Analyses