jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Cheng‐Wei Cheng | Yixuan Zhou | Wen‐Harn Pan | Supriya Dey | Chung‐Yi Wu | Wen‐Lian Hsu | Chi‐Huey Wong
Source: Nature Communications (article, 2018-11-30)
Field: Chemistry — Organic Chemistry

Hierarchical and programmable one-pot synthesis of oligosaccharides The programmable one-pot oligosaccharide synthesis method was designed to enable the rapid synthesis of a large number of oligosaccharides, using the software Optimer to search Building BLocks (BBLs) with defined relative reactivity values (RRVs) to be used sequentially in the one-pot reaction. However, there were only about 50 BBLs with measured RRVs in the original library and the method could only synthesize small oligosaccharides due to the RRV ordering requirement. Here, we increase the library to include 154 validated BBLs and more than 50,000 virtual BBLs with predicted RRVs by machine learning. We also develop the software Auto-CHO to accommodate more data handling and support hierarchical one-pot synthesis using fragments as BBLs generated by the one-pot synthesis. This advanced programmable one-pot method provides potential synthetic solutions for complex glycans with four successful examples demonstrated in this work. Software ; Computer science ; Programming language Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Chemical Synthesis and Analysis
Authors: Pablo Márquez-Neila | Chloe Fisher | Raphael Sznitman | Kevin Heng
Source: Nature Astronomy (article, 2018-06-22)
Field: Chemistry — Spectroscopy

Supervised machine learning for analysing spectra of exoplanetary atmospheres Exoplanet ; Computer science ; Hyperparameter optimization ; Opacity ; Machine learning ; Grid ; Artificial intelligence ; Algorithm ; Support vector machine ; Physics ; Mathematics ; Optics ; Stars ; Computer vision Spectroscopy and Laser Applications ; Stellar, planetary, and galactic studies ; Spectroscopy and Chemometric Analyses
Authors: Junji Seino | Ryo Kageyama | Mikito Fujinami | Yasuhiro Ikabata | Hiromi Nakai
Source: The Journal of Chemical Physics (article, 2018-03-15)
Field: Materials Science — Materials Chemistry

Semi-local machine-learned kinetic energy density functional with third-order gradients of electron density A semi-local kinetic energy density functional (KEDF) was constructed based on machine learning (ML). The present scheme adopts electron densities and their gradients up to third-order as the explanatory variables for ML and the Kohn-Sham (KS) kinetic energy density as the response variable in atoms and molecules. Numerical assessments of the present scheme were performed in atomic and molecular systems, including first- and second-period elements. The results of 37 conventional KEDFs with explicit formulae were also compared with those of the ML KEDF with an implicit formula. The inclusion of the higher order gradients reduces the deviation of the total kinetic energies from the KS calculations in a stepwise manner. Furthermore, our scheme with the third-order gradient resulted in the closest kinetic energies to the KS calculations out of the presented functionals. Kinetic energy ; Density functional theory ; Electron density ; Third order ; Orbital-free density functional theory ; Kinetic scheme ; Energy (signal processing) ; Electron ; Order (exchange) ; Variable (mathematics) ; Atomic physics ; Statistical physics ; Physics ; Hybrid functional ; Mathematics ; Chemistry ; Computational chemistry ; Classical mechanics ; Quantum mechanics ; Mathematical analysis Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Computational Drug Discovery Methods
Authors: Stavros Alexandros Theofanidis | Vladimir Galvita | Hilde Poelman | Naga Venkata Ranga Aditya Dharanipragada | Alessandro Longo | Maria Meledina | Gustaaf Van Tendeloo | Christophe Detavernier | Guy Marin
Source: ACS Catalysis (article, 2018-05-22)
Field: Materials Science — Materials Chemistry

Fe-Containing Magnesium Aluminate Support for Stability and Carbon Control during Methane Reforming We report a MgFexAl2–xO4 synthetic spinel, where x varies from 0 to 0.26, as support for Ni-based catalysts, offering stability and carbon control under various conditions of methane reforming. By incorporation of Fe into a magnesium aluminate spinel, a support is created with redox functionality and high thermal stability, as concluded from temporal analysis of products (TAP) experiments and redox cycling, respectively. A diffusion coefficient of 3 × 10–17 m2 s–1 was estimated for lattice oxygen at 993 K from TAP experiments. X-ray diffraction (XRD) and extended X-ray absorption fine structure (EXAFS) modeling identified that the incorporation of iron occurs as Fe3+ in the octahedral sites of the spinel lattice, replacing aluminum. Simulation of the X-ray absorption near edge structure (XANES) spectrum of the reduced support showed that 60 ± 10% of iron was reduced from 3+ to 2+ at 1073 K, while there was no formation of metallic iron. A series of Ni/MgFexAl2–xO4 catalysts, where x varies from 0 to 0.26, was synthesized and reduced, yielding a supported Ni-Fe alloy. The evolution of the catalyst structure during H2 temperature-programmed reduction (TPR) and CO2 temperature-programmed oxidation (TPO) was examined using time-resolved in situ XRD and XANES. During reforming, iron in both the support and alloy keeps control of carbon accumulation, as confirmed by O2-TPO on the spent catalysts. By fine tuning the amount of Fe in MgFexAl2–xO4, a supported alloy was obtained with a Ni/Fe molar ratio of ∼10, which was active for reforming and stable. By comparison of the performance of Ni-based catalysts with Fe either incorporated into or deposited onto the support, the location of Fe within the support proved crucial for the stability and carbon mitigation under reforming conditions. XANES ; Spinel ; Catalysis ; Materials science ; Redox ; Extended X-ray absorption fine structure ; Inorganic chemistry ; Steam reforming ; Aluminate ; Temperature-programmed reduction ; Methane ; Syngas ; X-ray absorption spectroscopy ; Analytical Chemistry (journal) ; Chemistry ; Metal ; Absorption spectroscopy ; Metallurgy ; Spectroscopy ; Hydrogen production Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Oxidation Reactions
Authors: Frady G. Adly | Hannah E. Bollard | Michael G. Gardiner | Ashraf Ghanem
Source: Catalysts (article, 2018-06-30)
Field: Chemistry — Organic Chemistry

Chiral Dirhodium(II) Carboxylates: New Insights into the Effect of Ligand Stereo-Purity on Catalyst Structure and Enantioselectivity The current report contributes to the understanding of the stereoselectivity of chiral dirhodium(II) carboxylate catalysts carrying N-protected tert-leucine ligands. Investigating the possible effect of ligand stereo-purity on catalyst structure and enantioselectivity was carried out. This was justified through a new X-ray crystal structure for Rh2(S,S,S,R-PTTL)4 diastereomer. Diastereomer ; Ligand (biochemistry) ; Chemistry ; Stereoselectivity ; Catalysis ; Carboxylate ; Stereochemistry ; Crystal structure ; Organic chemistry ; Receptor ; Biochemistry Cyclopropane Reaction Mechanisms ; Asymmetric Hydrogenation and Catalysis ; Asymmetric Synthesis and Catalysis
Authors: Shichao Zhang | Malcolm Xing | Bingyun Li
Source: International Journal of Molecular Sciences (review, 2018-06-01)
Field: Materials Science — Surfaces, Coatings and Films

Biomimetic Layer-by-Layer Self-Assembly of Nanofilms, Nanocoatings, and 3D Scaffolds for Tissue Engineering Achieving surface design and control of biomaterial scaffolds with nanometer- or micrometer-scaled functional films is critical to mimic the unique features of native extracellular matrices, which has significant technological implications for tissue engineering including cell-seeded scaffolds, microbioreactors, cell assembly, tissue regeneration, etc. Compared with other techniques available for surface design, layer-by-layer (LbL) self-assembly technology has attracted extensive attention because of its integrated features of simplicity, versatility, and nanoscale control. Here we present a brief overview of current state-of-the-art research related to the LbL self-assembly technique and its assembled biomaterials as scaffolds for tissue engineering. An overview of the LbL self-assembly technique, with a focus on issues associated with distinct routes and driving forces of self-assembly, is described briefly. Then, we highlight the controllable fabrication, properties, and applications of LbL self-assembly biomaterials in the forms of multilayer nanofilms, scaffold nanocoatings, and three-dimensional scaffolds to systematically demonstrate advances in LbL self-assembly in the field of tissue engineering. LbL self-assembly not only provides advances for molecular deposition but also opens avenues for the design and development of innovative biomaterials for tissue engineering. Nanotechnology ; Tissue engineering ; Materials science ; Scaffold ; Biomaterial ; Self-assembly ; Layer by layer ; Layer (electronics) ; Engineering ; Biomedical engineering Polymer Surface Interaction Studies ; 3D Printing in Biomedical Research ; Surface Modification and Superhydrophobicity
Authors: Sameh Ziad Ahmed Dabbak | Hazlee Azil Illias | Bee Chin Ang | Nurul Ain Abdul Latiff | Mohamad Zul Hilmey Makmud
Source: Energies (article, 2018-06-04)
Field: Materials Science — Materials Chemistry

Electrical Properties of Polyethylene/Polypropylene Compounds for High-Voltage Insulation In high-voltage insulation systems, the most commonly used material is polymeric material because of its high dielectric strength, high resistivity, and low dielectric loss in addition to good chemical and mechanical properties. In this work, various polymer compounds were prepared, consisting of low-density polyethylene (LDPE), high-density polyethylene (HDPE), polypropylene (PP), HDPE/PP, and LDPE/PP polymer blends. The relative permittivity and breakdown strength of each sample types were evaluated. In order to determine the physical properties of the prepared samples, the samples were also characterized using differential scanning calorimetry (DSC). The results showed that the dielectric constant of PP increased with the increase of HDPE and LDPE content. The breakdown measurement data for all samples were analyzed using the cumulative probability plot of Weibull distribution. From the acquired results, it was found that the dielectric strengths of LDPE and HDPE were higher than that of PP. Consequently, the addition of LDPE and HDPE to PP increased the breakdown strength of PP, but a variation in the weight ratio (30%, 50% and 70%) did not change significantly the breakdown strength. The DSC measurements showed two exothermic crystallization peaks representing two crystalline phases. In addition, the DSC results showed that the blended samples were physically bonded, and no co-crystallization occurred in the produced blends. Low-density polyethylene ; Materials science ; High-density polyethylene ; Composite material ; Polyethylene ; Polypropylene ; Differential scanning calorimetry ; Dielectric ; Crystallization ; Dielectric strength ; Crystallinity ; Chemistry ; Organic chemistry High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Lightning and Electromagnetic Phenomena
Authors: Qichen Xu | Zhenzhu Li | Miao Liu | Wan‐Jian Yin
Source: The Journal of Physical Chemistry Letters (article, 2018-11-27)
Field: Materials Science — Materials Chemistry

Rationalizing Perovskite Data for Machine Learning and Materials Design Machine learning has been recently used for novel perovskite designs owing to the availability of a large amount of perovskite formability data. Trustworthy results should be based on the valid and reliable data that can reveal the nature of materials as much as possible. In this study, a procedure has been developed to identify the formability of perovskites for all of the compounds with the stoichiometry of ABX<sub>3</sub> and (A'A″)(B'B'')X<sub>6</sub> that exist in experiments and are stored in the Materials Projects database. Our results have enriched the data of perovskite formability to a large extent and corrected the possible errors of previous data in ABO<sub>3</sub> compounds. Furthermore, machine learning with a multiple models approach has identified the A<sub>2</sub>B'B″O<sub>6</sub> compounds that have suspicious formability results in the current experimental data. Therefore, further experimental validation experiments are called for. This work paves a way for cleaning perovskite formability data for reliable machine-learning work in future. Perovskite (structure) ; Materials science ; Computer science ; Artificial intelligence ; Engineering ; Chemical engineering Machine Learning in Materials Science ; Perovskite Materials and Applications ; Electronic and Structural Properties of Oxides
Authors: Tarak K. Patra | Fu Zhang | Daniel S. Schulman | Henry Chan | Mathew J. Cherukara | Mauricio Terrones | Saptarshi Das | Badri Narayanan | Subramanian K. R. S. Sankaranarayanan
Source: ACS Nano (article, 2018-08-03)
Field: Materials Science — Materials Chemistry

Defect Dynamics in 2-D MoS<sub>2</sub> Probed by Using Machine Learning, Atomistic Simulations, and High-Resolution Microscopy Structural defects govern various physical, chemical, and optoelectronic properties of two-dimensional transition-metal dichalcogenides (TMDs). A fundamental understanding of the spatial distribution and dynamics of defects in these low-dimensional systems is critical for advances in nanotechnology. However, such understanding has remained elusive primarily due to the inaccessibility of (a) necessary time scales via standard atomistic simulations and (b) required spatiotemporal resolution in experiments. Here, we take advantage of supervised machine learning, in situ high-resolution transmission electron microscopy (HRTEM) and molecular dynamics (MD) simulations to overcome these limitations. We combine genetic algorithms (GA) with MD to investigate the extended structure of point defects, their dynamical evolution, and their role in inducing the phase transition between the semiconducting (2H) and metallic (1T) phase in monolayer MoS<sub>2</sub>. GA-based structural optimization is used to identify the long-range structure of randomly distributed point defects (sulfur vacancies) for various defect densities. Regardless of the density, we find that organization of sulfur vacancies into extended lines is the most energetically favorable. HRTEM validates these findings and suggests a phase transformation from the 2H-to-1T phase that is localized near these extended defects when exposed to high electron beam doses. MD simulations elucidate the molecular mechanism driving the onset of the 2H to 1T transformation and indicate that finite amounts of 1T phase can be retained by increasing the defect concentration and temperature. This work significantly advances the current understanding of defect structure/evolution and structural transitions in 2D TMDs, which is crucial for designing nanoscale devices with desired functionality. High-resolution transmission electron microscopy ; Molecular dynamics ; Materials science ; Chemical physics ; Crystallographic defect ; Monolayer ; Phase (matter) ; Transmission electron microscopy ; Phase transition ; Nanotechnology ; Nanoscopic scale ; Crystallography ; Condensed matter physics ; Chemistry ; Computational chemistry ; Physics 2D Materials and Applications ; MXene and MAX Phase Materials ; Machine Learning in Materials Science
Authors: Dipak Dutta | Andita Nataria Fitri Ganda | Jui-Kung Chih | Cheng-Chun Huang | Chung‐Jen Tseng | Ching‐Yuan Su
Source: Nanoscale (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Revisiting graphene–polymer nanocomposite for enhancing anticorrosion performance: a new insight into interface chemistry and diffusion model Graphene is impermeable to all molecules and has high chemical stability, which makes it an excellent anticorrosion coating for metals. However, current studies have indicated that galvanic coupling between graphene and a metal actually accelerates corrosion at the interface. Due to the insulating nature of polymers, graphene-polymer composite coatings with a strong interaction between the filler and the polymer matrix are an alternative means of addressing this issue. Nevertheless, such coatings require well-dispersed graphene flakes to lengthen the diffusion paths of gases or liquids, while preventing the formation of a conducting network from graphene to the metal. The difficulty in preparing such coatings was mainly due to problems with the control of the assembled phase during interfacial reactions. Herein, the interactions between the filler and the polymer were found to be a key factor governing anticorrosion performance, which has scarcely been previously reported. The advantage of graphene as a filler in anticorrosion coatings lies in its dispersibility and miscibility with both the casting solvent and the polymer. Electrochemically exfoliated graphene (EC-graphene) with appropriate surface functionalities that allow high miscibility with waterborne polyurethane (PU) and hydrophobic epoxy has been found to be an ideal filler that outperforms other graphene materials such as graphene oxide (GO) and reduced graphene oxide (rGO). Furthermore, a bilayer coating with EC-graphene additives for PU over epoxy has been found to reduce the corrosion rate (CR) to 1.81 × 10-5 mm per year. With a graphene loading of less than 1%, this represents the lowest CR ever achieved for copper and steel substrates and a diffusion coefficient that is lower by a factor of nearly 2.2 than that of the pristine polymer. Furthermore, we have shown that by controlling the amount of graphene loaded in the polymer galvanic corrosion favored by the formation of an interconnected graphene percolation network can successfully be limited. The present study, together with a facile and eco-friendly method of nanocomposite synthesis, may pave the way toward practical applications in the development of graphene-based anticorrosion coatings. Graphene ; Nanocomposite ; Interface (matter) ; Materials science ; Polymer nanocomposite ; Diffusion ; Nanotechnology ; Polymer ; Composite material ; Thermodynamics ; Physics Graphene research and applications ; Conducting polymers and applications ; 2D Materials and Applications
Authors: Oscar Valerio | Manjusri Misra | Amar K. Mohanty
Source: ACS Sustainable Chemistry & Engineering (review, 2018-03-28)
Field: Materials Science — Biomaterials

Poly(glycerol-<i>co</i>-diacids) Polyesters: From Glycerol Biorefinery to Sustainable Engineering Applications, A Review Upgrading of biobased glycerol to commercial products is a necessary step on sustainable development of oleaginous biomass biorefining. The synthesis of poly(glycerol-co-diacid) polyester materials is an attractive option for glycerol usage that can produce a wide range of products of commercial interest. These polymeric materials could be used on industrial applications as biomedical devices, surfactants and in thermoplastic material development. In this review, the process engineering aspects leading to tailorable polymeric products are comprehensively analyzed with emphasis on control of molecular architecture and functionality. Molecular weight, degree of branching, mechanical properties and surface chemistry of the materials can be controlled by fine-tuning synthesis procedures to match custom specifications in end products. Potential usage of poly(glycerol-co-diacid) materials with tailored physicochemical properties on industrially relevant applications is presented. Advantages and challenges in the synthesis of these novel polymeric materials for value added application are addressed and discussed. Biorefining ; Biorefinery ; Glycerol ; Polyester ; Raw material ; Materials science ; Thermoplastic ; Green chemistry ; Nanotechnology ; Process engineering ; Organic chemistry ; Chemistry ; Catalysis ; Composite material ; Engineering biodegradable polymer synthesis and properties ; Electrospun Nanofibers in Biomedical Applications ; Dendrimers and Hyperbranched Polymers
Authors: Marc Kielmann | Mathias O. Senge
Source: Angewandte Chemie International Edition (review, 2018-08-03)
Field: Materials Science — Materials Chemistry

Molecular Engineering of Free‐Base Porphyrins as Ligands—The N−H⋅⋅⋅X Binding Motif in Tetrapyrroles The core N-H units of planar porphyrins are often inaccessible to forming hydrogen-bonding complexes with acceptor molecules. This is due to the fact that the amine moieties are "shielded" by the macrocyclic system, impeding the formation of intermolecular H-bonds. However, methods exist to modulate the tetrapyrrole conformations and to reshape the vector of N-H orientation outwards, thus increasing their availability and reactivity. Strategies include the use of porpho(di)methenes and phlorins (calixphyrins), as well as saddle-distorted porphyrins. The former form cavities due to interruption of the aromatic system. The latter are highly basic systems and capable of binding anions and neutral molecules via N-H⋅⋅⋅X-type H-bonds. This Review discusses the role of porphyrin(oid) ligands in various coordination-type complexes, means to access the core for hydrogen bonding, the concept of conformational control, and emerging applications, such as organocatalysis and sensors. Porphyrin ; Chemistry ; Hydrogen bond ; Molecule ; Tetrapyrrole ; Intermolecular force ; Stereochemistry ; Free base ; Protonation ; Acceptor ; Crystallography ; Combinatorial chemistry ; Photochemistry ; Organic chemistry Porphyrin and Phthalocyanine Chemistry ; Molecular Sensors and Ion Detection ; Supramolecular Chemistry and Complexes
Authors: Pei Zhang | Augustinus J. J. Kragt | Albertus P. H. J. Schenning | Laurens T. de Haan | Guofu Zhou
Source: Journal of Materials Chemistry C (article, 2018-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

An easily coatable temperature responsive cholesteric liquid crystal oligomer for making structural colour patterns A crosslinkable, temperature-responsive cholesteric main-chain liquid crystal oligomer was prepared, and used to make patterned coatings. Oligomer ; Materials science ; Cholesteric liquid crystal ; Liquid crystal ; Chemical engineering ; Crystallography ; Nanotechnology ; Polymer chemistry ; Optoelectronics ; Chemistry Liquid Crystal Research Advancements ; Advanced Materials and Mechanics ; Photochromic and Fluorescence Chemistry