jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: John A. Hodge | Kumar Vijay Mishra | Amir I. Zaghloul
Source:  (article, 2019-11-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multi-Discriminator Distributed Generative Model for Multi-Layer RF Metasurface Discovery Metasurface-based antenna beam control is defining a new engineering paradigm in radio-frequency applications such as communications, radar, and analog spatial signal processing. Metasurfaces are composite electromagnetic material surfaces that are made of subwavelength scattering particles, or meta-atoms, with negligible thickness and optimized to control electromagnetic waves in unprecedented fashions through modified boundary conditions. Conventional metasurface design is a tedious process that requires iteratively solving Maxwell's equations. This becomes increasingly challenging as state-of-the-art metasurfaces require complex bi-anisotropic responses over multiple layers of meta- atoms and several frequency bands. In this paper, to reduce design time and optimization overhead, we employ a multi-discriminator distributed generative adversarial network for inverse design of multi- layer metasurfaces. Unlike conventional design approaches, our proposed approach is able to jointly design multiple layers, discover new meta- atom patterns, and avoid solving Maxwell's equations numerically or analytically. Results show that generated triple-layer meta-atoms can achieve frequency resonances within 7% of the input values. Discriminator ; Computer science ; Overhead (engineering) ; Antenna (radio) ; Radio frequency ; Radar ; Scattering ; Electronic engineering ; Physics ; Optics ; Telecommunications ; Engineering Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: Tatiana I. Spiridonova | Sergei I. Tverdokhlebov | Yuri G. Anissimov
Source: Journal of Pharmaceutical Sciences (article, 2019-04-11)
Field: Materials Science — Biomaterials

Investigation of the Size Distribution for Diffusion-Controlled Drug Release From Drug Delivery Systems of Various Geometries Drug delivery ; Diffusion ; Drug ; Materials science ; RADIUS ; Polymer ; Distribution (mathematics) ; Work (physics) ; Nanotechnology ; Controlled release ; Targeted drug delivery ; Thermodynamics ; Pharmacology ; Mathematics ; Composite material ; Physics ; Computer science ; Medicine Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems ; Drug Solubulity and Delivery Systems
Authors: Chuan Zhang | Jiashi Miao | Shuanglin Chen | Fan Zhang | Alan A. Luo
Source: Journal of Phase Equilibria and Diffusion (article, 2019-05-16)
Field: Materials Science — Biomaterials

CALPHAD-Based Modeling and Experimental Validation of Microstructural Evolution and Microsegregation in Magnesium Alloys During Solidification CALPHAD ; Materials science ; Microstructure ; Magnesium ; Metallurgy ; Casting ; Phase (matter) ; Dendrite (mathematics) ; Diffusion ; Thermodynamics ; Magnesium alloy ; Phase diagram ; Chemistry Magnesium Alloys: Properties and Applications ; Aluminum Alloy Microstructure Properties ; Aluminum Alloys Composites Properties
Authors: Jimmy Jiahong Kuo | Umut Aydemir | Jan‐Hendrik Pöhls | Fei Zhou | Guodong Yu | Alireza Faghaninia | Francesco Ricci | Mary Anne White | Gian‐Marco Rignanese | Geoffroy Hautier | Anubhav Jain | G. Jeffrey Snyder
Source: Journal of Materials Chemistry A (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Origins of ultralow thermal conductivity in 1-2-1-4 quaternary selenides Low thermal conductivity of BaAb<sub>2</sub>SnSe<sub>4</sub> is measured, which can be attributed to the weakly-bonded Ag–Ag dimers. Quaternary ; Thermal conductivity ; Materials science ; Geology ; Composite material ; Paleontology Advanced Thermoelectric Materials and Devices ; 2D Materials and Applications ; Chalcogenide Semiconductor Thin Films
Authors: Barry L. Smith | David M. Hughes | Abraham K. Badu‐Tawiah | Rebecca Eccles | Ian Goodall | Simon Maher
Source: Scientific Reports (article, 2019-05-29)
Field: Chemistry — Spectroscopy

Rapid Scotch Whisky Analysis and Authentication using Desorption Atmospheric Pressure Chemical Ionisation Mass Spectrometry Whisky, as a high value product, is often adulterated, with adverse economic effects for both producers and consumers as well as potential public health impacts. Here we report the use of DAPCI-MS to analyse and chemically profile both genuine and counterfeit whisky samples employing a novel 'direct from the bottle' methodology with zero sample pre-treatment, zero solvent requirement and almost no sample usage. 25 samples have been analysed from a collection of blended Scotch whisky (n = 15) and known counterfeit whisky products (n = 10). Principal component analysis has been applied to dimensionally reduce the data and discriminate between sample groups. Additional chemometric modelling, a partial least squares regression, has correctly classified samples with 92% success rate. DAPCI-MS shows promise for simple, fast and accurate counterfeit detection with potential for generic aroma profiling and process quality monitoring applications. Counterfeit ; Mass spectrometry ; Sample preparation ; Computer science ; Chromatography ; Environmental science ; Chemistry Mass Spectrometry Techniques and Applications ; Advanced Chemical Sensor Technologies ; Analytical Chemistry and Chromatography
Authors: Jasmi Kiiskinen | Arto Merivaara | Tiina Hakkarainen | Minna Kääriäinen | Susanna Miettinen | Marjo Yliperttula | Raili Koivuniemi
Source: Stem Cell Research & Therapy (article, 2019-09-23)
Field: Materials Science — Biomaterials

Nanofibrillar cellulose wound dressing supports the growth and characteristics of human mesenchymal stem/stromal cells without cell adhesion coatings As a result, NFC wound dressing offers a functional cell culture platform for hASCs to be used further for in vivo wound healing studies in the future. Mesenchymal stem cell ; Stem cell ; Viability assay ; Wound healing ; Cell biology ; Fibronectin ; Extracellular matrix ; Cell adhesion ; Stromal cell ; Cell growth ; Transplantation ; Tissue engineering ; Regenerative medicine ; Cell ; Materials science ; Chemistry ; Biomedical engineering ; Immunology ; Biology ; Pathology ; Medicine ; Surgery ; Biochemistry Electrospun Nanofibers in Biomedical Applications ; Mesenchymal stem cell research ; Wound Healing and Treatments
Authors: Ivana Nováčková | Dan Kučera | Jaromí­r Poří­zka | Iva Pernicová | Petr Sedláček | Martin Koller | Adriána Kovalcik | Stanislav Obruča
Source: Biochemical Engineering Journal (article, 2019-08-16)
Field: Materials Science — Biomaterials

Adaptation of Cupriavidus necator to levulinic acid for enhanced production of P(3HB-co-3HV) copolyesters Cupriavidus necator ; Polyhydroxyalkanoates ; Levulinic acid ; Strain (injury) ; Crystallinity ; Microorganism ; Biomass (ecology) ; Metabolic engineering ; Bacteria ; Adaptation (eye) ; Chemistry ; Biopolymer ; Materials science ; Polymer ; Food science ; Organic chemistry ; Biology ; Catalysis ; Enzyme ; Genetics biodegradable polymer synthesis and properties ; Catalysis for Biomass Conversion ; Biofuel production and bioconversion
Authors: Mathieu Mirjolet | V. Hari Babu | Lluís López‐Conesa | Sònia Estradé | F. Peiró | José Santiso | F. Sánchez | Pamela Machado | Pierluigi Gargiani | Manuel Valvidares | J. Fontcuberta
Source: Advanced Functional Materials (article, 2019-07-15)
Field: Materials Science — Materials Chemistry

Independent Tuning of Optical Transparency Window and Electrical Properties of Epitaxial SrVO<sub>3</sub> Thin Films by Substrate Mismatch Abstract Transparent metallic oxides are pivotal materials in information technology, photovoltaics, or even in architecture. They display the rare combination of metallicity and transparency in the visible range because of weak interband photon absorption and weak screening of free carriers to impinging light. However, the workhorse of current technology, indium tin oxide (ITO), is facing severe limitations and alternative approaches are needed. AMO 3 perovskites, M being a nd 1 transition metal, and A an alkaline earth, have a genuine metallic character and, in contrast to conventional metals, the electron–electron correlations within the nd 1 band enhance the carriers effective mass ( m *) and bring the transparency window limit (marked by the plasma frequency, ω p *) down to the infrared. Here, it is shown that epitaxial strain and carrier concentration allow fine tuning of optical properties (ω p *) of SrVO 3 films by modulating m * due to strain‐induced selective symmetry breaking of 3d‐t 2g ( xy , yz , xz ) orbitals. Interestingly, the DC electrical properties can be varied by a large extent depending on growth conditions whereas the optical transparency window in the visible is basically preserved. These observations suggest that the harsh conditions required to grow optimal SrVO 3 films may not be a bottleneck for their future application. Materials science ; Optoelectronics ; Epitaxy ; Opacity ; Thin film ; Band gap ; Substrate (aquarium) ; Electron mobility ; Indium tin oxide ; Sapphire ; Nanotechnology ; Optics ; Laser Electronic and Structural Properties of Oxides ; ZnO doping and properties ; Magnetic and transport properties of perovskites and related materials
Authors: Jacob E. Walley | Yuen-Onn Wong | Lucas A. Freeman | Diane A. Dickie | Robert J. Gilliard
Source: Catalysts (article, 2019-11-08)
Field: Chemistry — Organic Chemistry

N-Heterocyclic Carbene-Supported Aryl- and Alk- oxides of Beryllium and Magnesium Recently, we have witnessed significant progress with regard to the synthesis of molecular alkaline earth metal reagents and catalysts. To provide new precursors for light alkaline earth metal chemistry, molecular aryloxide and alkoxide complexes of beryllium and magnesium are reported. The reaction of beryllium chloride dietherate with two equivalents of 1,3-diisopropyl-4,5-dimethylimidizol-2-ylidine (sIPr) results in the formation of a bis(N-heterocyclic carbene) (NHC) beryllium dichloride complex, (sIPr)2BeCl2 (1). Compound 1 reacts with lithium diisopropylphenoxide (LiODipp) or sodium ethoxide (NaOEt) to form the terminal aryloxide (sIPr)Be(ODipp)2 (2) and alkoxide dimer [(sIPr)Be(OEt)Cl]2 (3), respectively. Compounds 2 and 3 represent the first beryllium alkoxide and aryloxide species supported by NHCs. Structurally related dimers of magnesium, [(sIPr)Mg(OEt)Brl]2 (4) and [(sIPr)Mg(OEt)Me]2 (5), were also prepared. Compounds 1-5 were characterized by single crystal X-ray diffraction studies, 1H, 13C, and 9Be NMR spectroscopy where applicable. Chemistry ; Carbene ; Magnesium ; Beryllium ; Alkoxide ; Alkaline earth metal ; Aryl ; Dimer ; Medicinal chemistry ; Inorganic chemistry ; Metal ; Crystallography ; Catalysis ; Organic chemistry ; Alkyl N-Heterocyclic Carbenes in Organic and Inorganic Chemistry ; Synthesis and characterization of novel inorganic/organometallic compounds ; Catalytic Cross-Coupling Reactions
Authors: Han Lin | Tony Pham | Mingjing Zhuo | Katherine A. Forrest | Shanelle Suepaul | Brian Space | Michael J. Zaworotko | Wei Shi | Yao Chen | Peng Cheng | Zhenjie Zhang
Source: ACS Applied Materials & Interfaces (article, 2019-06-11)
Field: Chemistry — Inorganic Chemistry

Molecular Sieving and Direct Visualization of CO<sub>2</sub> in Binding Pockets of an Ultramicroporous Lanthanide Metal–Organic Framework Platform Inspired by the structure of carbonic anhydrase, we developed a robust ultramicroporous lanthanide metal-organic framework (MOF) platform (NKMOF-3-Ln), which possesses a porous pocket to selectively bind with CO<sub>2</sub> at ambient conditions. Notably, CO<sub>2</sub> molecules can be precisely observed in the single-crystal structure of NKMOF-3-Ln. Highly ordered CO<sub>2</sub> molecules can strongly interact with the framework via electrostatic interaction of nitrates. We found that the CO<sub>2</sub> adsorption capacity and binding energy were gradually enhanced as lanthanide contraction. The strong CO<sub>2</sub> binding affinity endows NKMOF-3-Ln with excellent CO<sub>2</sub> separation performance, which is verified by experimental breakthrough results. Moreover, because of the specific binding affinity of CO<sub>2</sub>, NKMOF-3-Eu showed a fluorescence response to CO<sub>2</sub>. Lanthanide ; Materials science ; Metal-organic framework ; Metal ; Nanotechnology ; Visualization ; Inorganic chemistry ; Chemical engineering ; Adsorption ; Physical chemistry ; Organic chemistry ; Metallurgy ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Catalytic Processes in Materials Science
Authors: William P. Lustig | Simon J. Teat | Jing Li
Source: Journal of Materials Chemistry C (article, 2019-01-01)
Field: Chemistry — Inorganic Chemistry

Improving LMOF luminescence quantum yield through guest-mediated rigidification Rotation of a specific pyridyl ring in LMOF-236 is locked by loading guest molecules into the MOF's pore, improving quantum yield by nearly 400%–an example of a generalizable strategy for maximizing quantum yield <italic>via</italic> guest-packing rigidification. Quantum yield ; Yield (engineering) ; Luminescence ; Materials science ; Quantum ; Ring (chemistry) ; Molecule ; Nanotechnology ; Chemical engineering ; Crystallography ; Chemical physics ; Physics ; Chemistry ; Optoelectronics ; Organic chemistry ; Composite material ; Quantum mechanics ; Fluorescence ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics
Authors: Elżbieta Gońka | Long Yang | Ralf Steinbock | Fabio Pesciaioli | Rositha Kuniyil | Lutz Ackermann
Source: Chemistry - A European Journal (article, 2019-11-05)
Field: Chemistry — Organic Chemistry

π‐Extended Polyaromatic Hydrocarbons by Sustainable Alkyne Annulations through Double C−H/N−H Activation The widespread applications of substituted diketopyrrolopyrroles (DPPs) call for the development of efficient methods for their modular assembly. Herein, we present a π-expansion strategy for polyaromatic hydrocarbons (PAHs) by C-H activation in a sustainable fashion. Thus, twofold C-H/N-H activations were accomplished by versatile ruthenium(II)carboxylate catalysis, providing step-economical access to diversely decorated fluorogenic DPPs that was merged with late-stage palladium-catalyzed C-H arylation on the thus-assembled DPP motif. Catalysis ; Chemistry ; Alkyne ; Ruthenium ; Combinatorial chemistry ; Carboxylate ; Stereochemistry ; Organic chemistry Catalytic C–H Functionalization Methods ; Synthesis and Characterization of Pyrroles ; Synthesis of Indole Derivatives
Authors: Lokendra Khanal | Jennifer A. Sundararajan | You Qiang
Source: Energy Technology (article, 2019-11-28)
Field: Materials Science — Materials Chemistry

Advanced Nanomaterials for Nuclear Energy and Nanotechnology The use of the latest engineered nanomaterials in nuclear energy systems has opened doors for improving the performance and safety of nuclear power. Nuclear nanotechnology (NNT) deals with the use of engineered nanomaterials for future nuclear energy applications. Herein, the recent progress in research and benefits of using nanomaterials in different areas of nuclear energy like nuclear fuel extraction and fabrication, fission product capturing, creating robust reactor materials, radiation sensing and monitoring, and radioactive waste separation and spent nuclear fuel reprocessing are summarized. Ongoing research around the world in this field is reviewed, including experimental and computational methods. Nuclear power ; Nuclear fuel ; Radioactive waste ; Nuclear fission ; Nanomaterials ; Nanotechnology ; Nuclear fission product ; Nuclear fuel cycle ; Nuclear reactor ; Materials science ; Fission products ; Engineering ; Nuclear engineering ; Waste management ; Fission ; Physics ; Nuclear physics Nuclear Materials and Properties ; Ion-surface interactions and analysis ; Graphite, nuclear technology, radiation studies
Authors: Simon Roehrer | Mirjana Minceva
Source: Separations (article, 2019-07-24)
Field: Chemistry — Analytical Chemistry

Evaluation of Inter-Apparatus Separation Method Transferability in Countercurrent Chromatography and Centrifugal Partition Chromatography In the countercurrent chromatography and centrifugal partition chromatography, separation method transfer and scale-up is often described as an easy and straightforward procedure. Separation methods are usually developed on lab scale columns and subsequently transferred using linear scale-up factors to semi-preparative or preparative columns of the same column design. However, the separation methods described in the literature have been developed on various columns of different design and size. This is accompanied by differences in the separation behavior of the columns and therefore makes separation method transfer difficult. In the current study, the separation performances of different columns were evaluated and compared. Linear correlations of stationary phase retention and column efficiency as a function of flow rate were found to be applicable for the calculation of separation resolution in the typical operating range of each column. In this context, a two-point short-cut approach for a fast column characterization is recommended. This allows a quick prediction of the separation method transferability between columns, which saves experimental time and effort. In the current study, the transferability between five different columns from lab scale countercurrent chromatography (CCC) (18 mL) to semi-preparative centrifugal partition chromatography (CPCs) (250 mL) with different cell numbers and design is investigated. Countercurrent chromatography ; Chromatography ; Countercurrent exchange ; Transferability ; Partition (number theory) ; Separation (statistics) ; Volumetric flow rate ; Chemistry ; Context (archaeology) ; Chromatography column ; Column chromatography ; Computer science ; Mathematics ; Mechanics ; Physics Chromatography in Natural Products ; Natural product bioactivities and synthesis ; Pharmacological Effects of Natural Compounds
Authors: Benjamin Rizkin | Ryan L. Hartman
Source: Chemical Engineering Science (article, 2019-09-14)
Field: Materials Science — Materials Chemistry

Supervised machine learning for prediction of zirconocene-catalyzed α-olefin polymerization Polymerization ; Olefin polymerization ; Dispersity ; Artificial neural network ; Catalysis ; Metallocene ; Adiabatic process ; Reaction rate ; Olefin fiber ; Kinetic energy ; Materials science ; Thermodynamics ; Computer science ; Biological system ; Chemistry ; Polymer chemistry ; Organic chemistry ; Artificial intelligence ; Physics Machine Learning in Materials Science ; Organometallic Complex Synthesis and Catalysis ; Radioactive element chemistry and processing
Authors: Baekjun Kim | Sangwon Lee | Jihan Kim
Source: ChemRxiv (preprint, 2019-04-12)
Field: Materials Science — Materials Chemistry

Inverse Design in Porous Materials Using Artificial Neural Networks Generating optimal nanomaterials using artificial neural networks can potentially lead to a significant revolution in future materials design. Although progress has been made in creating small and simple molecules, complex materials such as crystalline porous materials have yet to be generated using any of the neural networks. In this work, we have for the first time implemented a generative adversarial network that uses a training set of 31,713 known zeolites to produce 14 crystalline porous materials. Our neural network takes in inputs in the form of energy and material dimensions and we show that zeolites with a user-desired range of 4 kJ/mol methane heat of adsorption can be reliably produced using our neural network. The fine-tuning of user-desired capability can potentially accelerate materials development as it demonstrates a successful case of inverse design in porous materials. Artificial neural network ; Inverse ; Porous medium ; Porosity ; Computer science ; Generative grammar ; Materials science ; Artificial intelligence ; Nanotechnology ; Process engineering ; Engineering ; Mathematics ; Composite material Machine Learning in Materials Science ; Anodic Oxide Films and Nanostructures ; Zeolite Catalysis and Synthesis
Authors: Jiaqi Wang | Ali Yousefzadi Nobakht | James Dean Blanks | Dongwon Shin | Sangkeun Lee | Amit Shyam | Hassan Rezayat | Seungha Shin
Source: Advanced Theory and Simulations (article, 2019-01-30)
Field: Materials Science — Materials Chemistry

Machine Learning for Thermal Transport Analysis of Aluminum Alloys with Precipitate Morphology Abstract A large number of microstructural parameters and a wide range of transport physics impose challenges on thermal transport analysis of alloy. Herein, modern data science techniques are employed to overcome the challenges, pursuing effective calculation of thermal transport properties. This emerging approach is tested for precipitate‐hardened aluminum (Al) alloy with consideration of precipitate morphology. The finite element method (FEM) is employed to create a database of effective thermal conductivity of hypothetical Al alloys with varying precipitate morphological and thermal transport features. Using the FEM‐generated data sets, the correlation analysis is conducted to qualitatively evaluate the importance of various precipitate features. The correlation analysis identifies the surface area, average diameter, and volume fraction of precipitates as the most descriptive features for determining the thermal conductivity of alloys. Afterward machine learning (ML) models are trained to accurately predict the effective thermal conductivity. Comparing the ML predictions with effective thermal conductivity and microstructural information from experiments, precipitate thermal transport properties can be calculated, such as interfacial conductance between Al matrix and precipitate, without atomistic simulations. This research demonstrates the feasibility of data‐driven approaches for effective thermal transport calculation and the promise of the FEM‐generated data analysis for more comprehensive evaluation of metallic alloys. Thermal conductivity ; Materials science ; Alloy ; Volume fraction ; Precipitation ; Thermal ; Finite element method ; Thermal analysis ; Aluminium ; Metallurgy ; Composite material ; Thermodynamics ; Physics ; Meteorology Thermal properties of materials ; Aluminum Alloy Microstructure Properties ; Machine Learning in Materials Science
Authors: Jing Zhang | Qin-Wei Tang | Ding Liu
Source: IEEE Transactions on Semiconductor Manufacturing (article, 2019-03-21)
Field: Materials Science — Materials Chemistry

Research Into the LSTM Neural Network-Based Crystal Growth Process Model Identification In this paper, a model identification method based on a long short-term memory (LSTM) neural network composed of a network structure and training algorithm is used to build a thermal field model that accurately simulates the crystal growth process. The support vector machine (SVM) approach is then adopted to identify model order and lag to determine network input and to improve precision. The thermal field model reflecting the growth process in the Czochralski crystal furnace is simulated. Experimental results and comparative analysis results both suggest that the method proposed by this paper can build an efficient thermal field model which outperforms other methods in terms of precision. Artificial neural network ; Support vector machine ; Process (computing) ; Field (mathematics) ; Computer science ; Identification (biology) ; Artificial intelligence ; Thermal ; Lag ; Data mining ; Network model ; Machine learning ; Algorithm ; Pattern recognition (psychology) ; Mathematics Crystallization and Solubility Studies ; Metallurgical Processes and Thermodynamics ; Advanced Control Systems Optimization