jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Christine Guéneau | N. Dupin | Lina Kjellqvist | E. Geiger | Masaki Kurata | Stéphane Gossé | E. C. Corcoran | Andrea Quaini | P.R. Hania | Anna L. Smith | M.H.A. Piro | Theodore M. Besmann | P. E. A. Turchi | Julie Dumas | M. J. Welland | Tsutomu Ogata | B.O. Lee | Jacob Kennedy | Cynthia A. Adkins | Mark Bankhead | Davide Costa
Source: Calphad (article, 2020-11-11)
Field: Materials Science — Materials Chemistry

TAF-ID: An international thermodynamic database for nuclear fuels applications CALPHAD ; Database ; MOX fuel ; Thermochemistry ; Nitride ; Fission products ; Materials science ; Carbide ; Nuclear fission product ; Nuclear engineering ; Plutonium ; Chemistry ; Radiochemistry ; Metallurgy ; Computer science ; Physical chemistry ; Nanotechnology ; Engineering Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Radioactive element chemistry and processing
Authors: Thomas Ursby | Karl Åhnberg | Roberto Appio | Oskar Aurelius | A. Barczyk | Antonio Bartalesi | Monika Bjelčić | Fredrik Bolmsten | Yngve Cerenius | R. Bruce Doak | Mikel Eguiraun | Thomas Eriksson | Ross J. Friel | Ishkhan Gorgisyan | Andrea Gross | Vahid Haghighat | Franz Hennies | E. Jagudin | B.N. Jensen | Tobias Jeppsson | Marco Kloos | Julio Lidón-Simon | G.M.A. Lima | Robert Lizatović | M. Lundin | Antonio Milàn-Otero | Mirko Milas | Jie Nan | Alberto Nardella | Anders Rosborg | Anastasya Shilova | Robert L. Shoeman | Frank Siewert | P. Sondhauss | V. Talibov | Hamed Tarawneh | Johan Thånell | Marjolein Thunnissen | Johan Unge | Christopher D. Ward | Ana González | U. Müeller
Source: Journal of Synchrotron Radiation (article, 2020-08-05)
Field: Materials Science — Materials Chemistry

BioMAX – the first macromolecular crystallography beamline at MAX IV Laboratory BioMAX is the first macromolecular crystallography beamline at the MAX IV Laboratory 3 GeV storage ring, which is the first operational multi-bend achromat storage ring. Due to the low-emittance storage ring, BioMAX has a parallel, high-intensity X-ray beam, even when focused down to 20 µm × 5 µm using the bendable focusing mirrors. The beam is tunable in the energy range 5-25 keV using the in-vacuum undulator and the horizontally deflecting double-crystal monochromator. BioMAX is equipped with an MD3 diffractometer, an ISARA high-capacity sample changer and an EIGER 16M hybrid pixel detector. Data collection at BioMAX is controlled using the newly developed MXCuBE3 graphical user interface, and sample tracking is handled by ISPyB. The computing infrastructure includes data storage and processing both at MAX IV and the Lund University supercomputing center LUNARC. With state-of-the-art instrumentation, a high degree of automation, a user-friendly control system interface and remote operation, BioMAX provides an excellent facility for most macromolecular crystallography experiments. Serial crystallography using either a high-viscosity extruder injector or the MD3 as a fixed-target scanner is already implemented. The serial crystallography activities at MAX IV Laboratory will be further developed at the microfocus beamline MicroMAX, when it comes into operation in 2022. MicroMAX will have a 1 µm × 1 µm beam focus and a flux up to 10<sup>15</sup> photons s<sup>-1</sup> with main applications in serial crystallography, room-temperature structure determinations and time-resolved experiments. Beamline ; Crystallography ; X-ray crystallography ; Macromolecule ; Chemistry ; Materials science ; Physics ; Diffraction ; Optics ; Biochemistry Enzyme Structure and Function ; Advanced Electron Microscopy Techniques and Applications ; Advanced X-ray Imaging Techniques
Authors: Dimitri Álvarez‐Dorta | David Deniaud | Mathieu Mével | Sébastien G. Gouin
Source: Chemistry - A European Journal (review, 2020-06-15)
Field: Chemistry — Organic Chemistry

Tyrosine Conjugation Methods for Protein Labelling Over the last two decades, the development of chemical biology and the need for more defined protein conjugates have fostered active research on new bioconjugation techniques. In particular, a wide range of biorthogonal labelling strategies have been reported to functionalise the phenol side chain of tyrosines (Tyr). Tyr occur at medium frequency and are partially buried at the protein surface, offering interesting opportunities for site-selective labelling of the most reactive residues. Tyr-targeting has proved effective for designing a wide range of important biomolecules including antibody-drug conjugates, fluorescent or radioactive protein probes, glycovaccines, protein aggregates, and PEG conjugates. Innovative methods have also been reported for site-specific labelling with ligand-directed anchors and for the specific affinity capture of proteins. This review will present and discuss these promising alternatives to the conventional labelling of the nucleophilic lysine and cysteine residues. Bioconjugation ; Labelling ; Biomolecule ; Conjugate ; Chemistry ; Cysteine ; Tyrosine ; Lysine ; Combinatorial chemistry ; Biochemistry ; Fluorescence ; Amino acid ; Enzyme Click Chemistry and Applications ; Monoclonal and Polyclonal Antibodies Research ; Chemical Synthesis and Analysis
Authors: Bouthayna Zilate | Christian Fischer | Christof Sparr
Source: Chemical Communications (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Design and application of aminoacridinium organophotoredox catalysts Recent developments in preparative photocatalysis have reshaped synthetic strategies and now represent an integral part of current organic chemistry. Due to their favourable electrochemical and photophysical properties, the nowadays most frequently used photocatalysts are based on precious Ru- and Ir-polypyridyl complexes. Apart from that, organic catalysts such as the acridinium salts are now commonly employed to complement transition metals to provide potentially sustainable strategies amenable to large-scale synthesis. In this feature article, the design, synthesis and application of aminoacridinium photoredox catalysts as well as their exceptionally broad range of redox properties are highlighted. Due to their modularity, this burgeoning class of organophotocatalysts is anticipated to contribute significantly to synthetic methodology development and the translation to a wide range of innovative implementations. Catalysis ; Chemistry ; Combinatorial chemistry ; Chemical engineering ; Organic chemistry ; Engineering Radical Photochemical Reactions ; Oxidative Organic Chemistry Reactions ; Sulfur-Based Synthesis Techniques
Authors: Jingnan Zheng | Xiang Sun | Chenglong Qiu | Yi‐Long Yan | Zihao Yao | Shengwei Deng | Xing Zhong | Gui‐Lin Zhuang | Zhongzhe Wei | Jianguo Wang
Source: The Journal of Physical Chemistry C (article, 2020-05-29)
Field: Materials Science — Materials Chemistry

High-Throughput Screening of Hydrogen Evolution Reaction Catalysts in MXene Materials In this study, machine learning (ML) models combined with density functional theory (DFT) calculations and Gibbs free energy of hydrogen adsorption (ΔGH*) were employed to facilitate the high-throughput screening of hydrogen evolution reaction (HER) catalysts in various MXene materials. The predicted ΔGH* values show a high-level accuracy via the random forest algorithm by using only simple elemental features. A total of 299 MXene materials were screened by DFT calculations and four ML models (Elman Artificial Neural Networks, kernel ridge regression, support vector regression, and random forest regression algorithms). Using the simple elemental information, the random forest algorithm shows a high-level predicted accuracy with a low testing root-mean-square error of 0.27 eV. Os2B- and S-terminated Scn+1Nn (n = 1, 2, 3) were discovered to be the active catalysts as ΔGH* approaches zero with wide hydrogen coverages (θ from 1/9 to 4/9). S functional groups play a crucial role in regulating the HER performance due to the antibonding states which are full of electrons. Consequently, it weakens the adsorption of H* which is the key step of HER. In summary, the present work suggests that ML models are competitive tools in accelerating the screening of efficient HER catalysts. Density functional theory ; Random forest ; Antibonding molecular orbital ; Catalysis ; Gibbs free energy ; Artificial neural network ; Support vector machine ; Throughput ; Materials science ; Hydrogen ; Computer science ; Adsorption ; Chemistry ; Electron ; Biological system ; Machine learning ; Computational chemistry ; Physical chemistry ; Thermodynamics ; Physics ; Atomic orbital ; Quantum mechanics MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques ; Ammonia Synthesis and Nitrogen Reduction
Authors: Natasa P. Kalogiouri | Reza Aalizadeh | Marilena E. Dasenaki | Νikolaos S. Τhomaidis
Source: Analytica Chimica Acta (review, 2020-07-30)
Field: Chemistry — Analytical Chemistry

Application of High Resolution Mass Spectrometric methods coupled with chemometric techniques in olive oil authenticity studies - A review Chemometrics ; Principal component analysis ; Linear discriminant analysis ; Pattern recognition (psychology) ; Artificial intelligence ; Chemistry ; Olive oil ; Artificial neural network ; Cluster analysis ; Chromatography ; Computer science ; Food science Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Advanced Chemical Sensor Technologies
Authors: Yun Zhang | Xiaojie Xu
Source: AIP Advances (article, 2020-03-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Machine learning the magnetocaloric effect in manganites from compositions and structural parameters Solid-state refrigeration techniques have drawn increasing attention due to their potential for improving the energy efficiency of refrigeration and temperature-control systems without using harmful gas as in conventional gas compression techniques. Research on magnetocaloric lanthanum manganites with near-room-temperature Curie temperature shows promising results for development of magnetic refrigeration devices. Chemical substitutions are one of the most effective methods to tune the magnetocaloric effect, represented by the maximum magnetic entropy change (MMEC), through the incorporation of various lanthanides, rare-earth elements, alkali metals, alkaline-earth metals, transition metals, and other elements. Some theories based on lattice distortions and double-exchange interactions show that ionic radii of the dopants and final compositions correlate with the MMEC, but the correlations are generally limited to A-site substitutions and become less applicable to multi-doped manganites than single-doped ones. In this work, the Gaussian process regression model is developed as a machine learning tool to find statistical correlations between the MMEC and structural parameters among lanthanum manganites. More than 70 lattices, cubic, pseudocubic, orthorhombic, and rhombohedral, with the MMEC ranging from 0.65 J kg−1 K−1 to 8.00 J kg−1 K−1 under a field change of 5 T are explored for this purpose. Structural parameters utilized as descriptors include ionic radii at both A- and B-sites, ⟨Mn–O⟩ bond length, ⟨Mn–O–Mn⟩ bond angle, and compositions consisting of up to six elements. The modeling approach demonstrates a high degree of accuracy and stability, contributing to efficient and low-cost estimations of the magnetocaloric effect. Magnetic refrigeration ; Ionic radius ; Orthorhombic crystal system ; Curie temperature ; Dopant ; Materials science ; Refrigeration ; Thermodynamics ; Lattice energy ; Doping ; Condensed matter physics ; Magnetization ; Crystal structure ; Chemistry ; Ion ; Ferromagnetism ; Magnetic field ; Crystallography ; Physics Magnetic and transport properties of perovskites and related materials ; Advanced Condensed Matter Physics ; Multiferroics and related materials
Authors: Lucas S. Palacios | S. Tchoumakov | Maria Guix | Ignacio Pagonabarraga | Samuel Sánchez | Adolfo G. Grushin
Source: arXiv (Cornell University) (article, 2020-12-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Guided accumulation of active particles by topological design of a second-order skin effect Collective guidance of out-of-equilibrium systems without using external fields is a challenge of paramount importance in active matter, ranging from bacterial colonies to swarms of self-propelled particles. Designing strategies to guide active matter and exploiting enhanced diffusion associated to its motion will provide insights for application from sensing, drug delivery to water remediation. However, achieving directed motion without breaking detailed balance, for example by asymmetric topographical patterning, is challenging. Here we engineer a two-dimensional periodic topographical design with detailed balance in its unit cell where we observe spontaneous particle edge guidance and corner accumulation of self-propelled particles. This emergent behaviour is guaranteed by a second-order non-Hermitian skin effect, a topologically robust non-equilibrium phenomenon, that we use to dynamically break detailed balance. Our stochastic circuit model predicts, without fitting parameters, how guidance and accumulation can be controlled and enhanced by design: a device guides particles more efficiently if the topological invariant characterizing it is non-zero. Our work establishes a fruitful bridge between active and topological matter, and our design principles offer a blueprint to design devices that display spontaneous, robust and predictable guided motion and accumulation, guaranteed by out-of-equilibrium topology. Active matter ; Topology (electrical circuits) ; Computer science ; Detailed balance ; Physics ; Statistical physics ; Mathematics Metamaterials and Metasurfaces Applications ; Topological Materials and Phenomena ; Orbital Angular Momentum in Optics
Authors: Junhui Zhang | Lixiong Dai | Alexandra M. Webster | Wesley Ting Kwok Chan | Lewis E. MacKenzie | Róbert Pál | Steven L. Cobb | Ga‐Lai Law
Source: Angewandte Chemie International Edition (article, 2020-09-22)
Field: Materials Science — Materials Chemistry

Unusual Magnetic Field Responsive Circularly Polarized Luminescence Probes with Highly Emissive Chiral Europium(III) Complexes Chirality is ubiquitous within biological systems where many of the roles and functions are still undetermined. Given this, there is a clear need to design and develop sensitive chiral optical probes that can function within a biological setting. Here we report the design and synthesis of magnetically responsive Circularly Polarized Luminescence (CPL) complexes displaying exceptional photophysical properties (quantum yield up to 31 % and |g<sub>lum</sub> | up to 0.240) by introducing chiral substituents onto the macrocyclic scaffolds. Magnetic CPL responses are observed in these chiral Eu<sup>III</sup> complexes, promoting an exciting development to the field of magneto-optics. The |g<sub>lum</sub> | of the <sup>5</sup> D<sub>0</sub> → <sup>7</sup> F<sub>1</sub> transition increases by 20 % from 0.222 (0 T) to 0.266 (1.4 T) displaying a linear relationship between the Δg<sub>lum</sub> and the magnetic field strength. These Eu<sup>III</sup> complexes with magnetic CPL responses, provides potential development to be used in CPL imaging applications due to improved sensitivity and resolution. Luminescence ; Europium ; Circular polarization ; Magnetic circular dichroism ; Magnetic field ; Materials science ; Photochemistry ; Chemistry ; Optoelectronics ; Physics ; Astronomy Lanthanide and Transition Metal Complexes ; Magnetism in coordination complexes ; Advanced NMR Techniques and Applications
Authors: Liang Pan | Fan Wang | Yuan Cheng | Wan Ru Leow | Yong‐Wei Zhang | Ming Wang | Pingqiang Cai | Baohua Ji | Dechang Li | Xiaodong Chen
Source: Nature Communications (article, 2020-03-12)
Field: Materials Science — Biomaterials

A supertough electro-tendon based on spider silk composites Compared to transmission systems based on shafts and gears, tendon-driven systems offer a simpler and more dexterous way to transmit actuation force in robotic hands. However, current tendon fibers have low toughness and suffer from large friction, limiting the further development of tendon-driven robotic hands. Here, we report a super tough electro-tendon based on spider silk which has a toughness of 420 MJ/m<sup>3</sup> and conductivity of 1,077 S/cm. The electro-tendon, mechanically toughened by single-wall carbon nanotubes (SWCNTs) and electrically enhanced by PEDOT:PSS, can withstand more than 40,000 bending-stretching cycles without changes in conductivity. Because the electro-tendon can simultaneously transmit signals and force from the sensing and actuating systems, we use it to replace the single functional tendon in humanoid robotic hand to perform grasping functions without additional wiring and circuit components. This material is expected to pave the way for the development of robots and various applications in advanced manufacturing and engineering. Tendon ; Materials science ; Spider silk ; Composite material ; Toughness ; Bending ; Limiting ; Carbon nanotube ; SILK ; PEDOT:PSS ; Tearing ; Computer science ; Mechanical engineering ; Polymer ; Engineering ; Anatomy Silk-based biomaterials and applications ; Adhesion, Friction, and Surface Interactions ; Advanced Sensor and Energy Harvesting Materials
Authors: Bingnan Qian | Jinyong Zhang | Yangyang Fu | Fan Sun | Yuan Wu | Jun Cheng | P. Vermaut | F. Prima
Source: Journal of Material Science and Technology (article, 2020-07-15)
Field: Materials Science — Materials Chemistry

In-situ microstructural investigations of the TRIP-to-TWIP evolution in Ti-Mo-Zr alloys as a function of Zr concentration Twip ; Materials science ; Crystal twinning ; Plasticity ; Deformation mechanism ; Microstructure ; Metallurgy ; Electron backscatter diffraction ; Deformation (meteorology) ; Ductility (Earth science) ; Work hardening ; Alloy ; Composite material ; Creep Titanium Alloys Microstructure and Properties ; Intermetallics and Advanced Alloy Properties ; Advanced materials and composites
Authors: Ruiyang Li | Eungkyu Lee | Tengfei Luo
Source: Materials Today Physics (article, 2020-01-28)
Field: Materials Science — Materials Chemistry

A unified deep neural network potential capable of predicting thermal conductivity of silicon in different phases Thermal conductivity ; Materials science ; Silicon ; Artificial neural network ; Ab initio ; Molecular dynamics ; Phase transition ; Work (physics) ; Field (mathematics) ; Thermal ; Phase (matter) ; Amorphous solid ; Force field (fiction) ; Statistical physics ; Computer science ; Artificial intelligence ; Thermodynamics ; Computational chemistry ; Physics ; Chemistry ; Optoelectronics ; Mathematics Machine Learning in Materials Science ; Thermal properties of materials ; Semiconductor materials and devices
Authors: Jose Recatala‐Gomez | Ady Suwardi | Iris Nandhakumar | Anas Abutaha | Kedar Hippalgaonkar
Source: ACS Applied Energy Materials (article, 2020-01-29)
Field: Materials Science — Materials Chemistry

Toward Accelerated Thermoelectric Materials and Process Discovery Thermoelectric materials have the ability to convert heat energy to electrical power and vice versa. While the thermodynamic upper limit is defined by the Carnot efficiency, the material figure of merit, zT, is far from this theoretical limit, typically limited by a complex interplay of non-equilibrium charge and phonon-scattering. Materials innovation is a slow, arduous process due to the complex correlations between crystal structure, microstructure engineering, and thermoelectric properties. Many physical concepts and materials have been unearthed in this path to discovery, supported ably by innovations in technology over many decades, revealing important material and transport descriptors. In this review, we look back at some case studies of inorganic thermoelectric materials employing a bird’s-eye view of complementary advancements in scientific concepts and technological advancements and conclude that most high values of zT have emerged from developed scientific models fueled by moderately mature technologies. On the basis of this conclusion, we then propose that the recent emergence of data-driven approaches and high-throughput experiments, encompassing synthesis as well as characterization, with machine learning guided inverse design is perfectly suited to provide an accelerated pathway toward the discovery of next-generation thermoelectric materials, potentially providing a feasible alternative source of energy for a sustainable future. Thermoelectric effect ; Thermoelectric materials ; Process (computing) ; Computer science ; Characterization (materials science) ; Carnot cycle ; Figure of merit ; Limit (mathematics) ; Engineering physics ; Nanotechnology ; Materials science ; Physics Advanced Thermoelectric Materials and Devices ; Machine Learning in Materials Science ; Thermal properties of materials
Authors: Camelia Berghian-Groșan | Dana Alina Măgdaş
Source: Talanta (article, 2020-05-21)
Field: Chemistry — Analytical Chemistry

Raman spectroscopy and machine-learning for edible oils evaluation Chemistry ; Edible oil ; Raman spectroscopy ; Food science ; Sunflower ; Pulp and paper industry ; Sunflower oil ; Agricultural engineering ; Biochemical engineering ; Horticulture ; Engineering Spectroscopy and Chemometric Analyses ; Edible Oils Quality and Analysis ; Phytochemical and Pharmacological Studies
Authors: Minzhen Feng | Wei Lu | Yun Zhou | Ranran Zhen | Hongmei He | Ya Wang | Chunmei Li
Source: Scientific Reports (article, 2020-09-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Synthesis of polypyrrole/nitrogen-doped porous carbon matrix composite as the electrode material for supercapacitors Abstract Polypyrrole complex nitrogen-doped porous carbon matrix (PPy/N-PCM) was synthesized by a simple two-step method. Firstly, graphene oxide was prepared by the modified Hummers method. Secondly, Polypyrrole was compounded on the graphene oxide substrate, and the carbon matrix with a high specific surface area was obtained through high-temperature carbonization and KOH activation, and polypyrrole was used as a nitrogen source for the final nitrogen-doped composite material. The structure characterization of the carbon matrix and the final composite material shows that the carbon matrix surface has obvious porous structure, and the polypyrrole nanospheres grow uniformly on the porous carbon matrix surface. The electrochemical evaluation show that the prepared PPy/N-PCM has excellent supercapacitor performance, and its specific capacitance can reach 237.5 F g −1 . When the current density reaches 10 A g −1 , it has good cycle stability (the capacitance retention after 1000 charge and discharge is 88.53% of the initial capacitance value, which is better than pure PPy-60.76% and PPy/rGO-C-71.84%). The excellent capacitance performance, good-looking micro-morphology and simple synthesis method of the PPy/N-PCM provide the possibility for its commercialization. Polypyrrole ; Materials science ; Supercapacitor ; Graphene ; Carbonization ; Capacitance ; Chemical engineering ; Carbon fibers ; Composite number ; Specific surface area ; Oxide ; Composite material ; Electrode ; Nanotechnology ; Polymer ; Polymerization ; Chemistry ; Organic chemistry ; Scanning electron microscope Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Electrocatalysts for Energy Conversion