jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Vahid Daghigh | Thomas E. Lacy | Hamid Daghigh | Grace X. Gu | Kourosh T. Baghaei | M.F. Horstemeyer | Charles U. Pittman
Source: Journal of Reinforced Plastics and Composites (article, 2020-04-27)
Field: Materials Science — Polymers and Plastics

Machine learning predictions on fracture toughness of multiscale bio-nano-composites Tailorability is an important advantage of composites. Incorporating new bio-reinforcements into composites can contribute to using agricultural wastes and creating tougher and more reliable materials. Nevertheless, the huge number of possible natural material combinations works against finding optimal composite designs. Here, machine learning was employed to effectively predict fracture toughness properties of multiscale bio-nano-composites. Charpy impact tests were conducted on composites with various combinations of two new bio fillers, pistachio shell powders, and fractal date seed particles, as well as nano-clays and short latania fibers, all which reinforce a poly(propylene)/ethylene–propylene–diene-monomer matrix. The measured energy absorptions obtained were used to calculate strain energy release rates as a fracture toughness parameter using linear elastic fracture mechanics and finite element analysis approaches. Despite the limited number of training data obtained from these impact tests and finite element analysis, the machine learning results were accurate for prediction and optimal design. This study applied the decision tree regressor and adaptive boosting regressor machine learning methods in contrast to the K-nearest neighbor regressor machine learning approach used in our previous study for heat deflection temperature predictions. Scanning electron microscopy, optical microscopy, and transmission electron microscopy were used to study the nano-clay dispersion and impact fracture morphology. Materials science ; Composite material ; Fracture toughness ; Toughness ; Charpy impact test ; Scanning electron microscope ; Fracture mechanics ; Fracture (geology) ; Composite number Natural Fiber Reinforced Composites ; Mechanical Behavior of Composites ; Bamboo properties and applications
Authors: B. Roter | S. V. Dordevic
Source: Physica C Superconductivity (article, 2020-05-27)
Field: Materials Science — Materials Chemistry

Predicting new superconductors and their critical temperatures using machine learning Superconductivity ; Condensed matter physics ; Artificial intelligence ; Computer science ; Materials science ; Psychology ; Physics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Advanced Physical and Chemical Molecular Interactions
Authors: Hiu Yung Wong | Ming Xiao | Boyan Wang | Yan Ka Chiu | Xiaodong Yan | Jiahui Ma | Kohei Sasaki | Han Wang | Yuhao Zhang
Source: IEEE Journal of the Electron Devices Society (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

TCAD-Machine Learning Framework for Device Variation and Operating Temperature Analysis With Experimental Demonstration This work, for the first time, experimentally demonstrates a TCAD-Machine Learning (TCAD-ML) framework to assist the analysis of device-to-device variation and operating (ambient) temperature without the need of physical quantities extraction. The ML algorithm used in this work is the Principal Component Analysis (PCA) followed by third order polynomial regression. After calibrated to limited `expensive' experimental data, `low cost' TCAD simulation is used to generate a large amount of device data to train the ML model. The ML was then used to identify the root cause of device variation and operating temperature from any given experimental current-voltage (I-V) characteristics. We applied this framework to study the ultra-wide-bandgap gallium oxide (Ga2O3) Schottky barrier diode (SBD), an emerging device technology that holds great promise for temperature sensing, RF, and power applications in harsh environments. After calibration, over 150,000 electrothermal TCAD simulations are performed with random variation of physical parameters (anode effective work function, drift layer doping, and drift layer thickness) and operating temperature. An ML model is trained using these TCAD data and we found 1,000-10,000 TCAD data can train an accurate machine. We show that without physical quantities extraction, performing PCA is essential for the TCAD trained ML model to be applicable to analyze experimental characteristics. The physical parameters and temperatures predicted by the ML model show good agreement with experimental analysis. Our TCAD-ML framework shows great promise to accelerate the development of new device technologies with a significantly more efficient process of material and device experimentation. Variation (astronomy) ; Computer science ; Materials science ; Electronic engineering ; Optoelectronics ; Physics ; Engineering Ga2O3 and related materials ; Gas Sensing Nanomaterials and Sensors ; Perovskite Materials and Applications
Authors: Alireza Taghizadeh | Ulrik Leffers | Thomas G. Pedersen | Kristian S. Thygesen
Source: Nature Communications (article, 2020-06-15)
Field: Materials Science — Materials Chemistry

A library of ab initio Raman spectra for automated identification of 2D materials Raman spectroscopy is frequently used to identify composition, structure and layer thickness of 2D materials. Here, we describe an efficient first-principles workflow for calculating resonant first-order Raman spectra of solids within third-order perturbation theory employing a localized atomic orbital basis set. The method is used to obtain the Raman spectra of 733 different monolayers selected from the Computational 2D Materials Database (C2DB). We benchmark the computational scheme against available experimental data for 15 known monolayers. Furthermore, we propose an automatic procedure for identifying a material based on an input experimental Raman spectrum and apply it to the cases of MoS<sub>2</sub> (H-phase) and WTe<sub>2</sub> (T[Formula: see text]-phase). The Raman spectra of all materials at different excitation frequencies and polarization configurations are freely available from the C2DB. Our comprehensive and easily accessible library of ab initio Raman spectra should be valuable for both theoreticians and experimentalists in the field of 2D materials. Raman spectroscopy ; Ab initio ; Spectral line ; Ab initio quantum chemistry methods ; Coherent anti-Stokes Raman spectroscopy ; Perturbation theory (quantum mechanics) ; Polarization (electrochemistry) ; Excitation 2D Materials and Applications ; Topological Materials and Phenomena ; Graphene research and applications
Authors: Cristina Belda Marín | Vincent Fitzpatrick | David L. Kaplan | Jessem Landoulsi | Erwann Guénin | Christophe Egles
Source: Frontiers in Chemistry (review, 2020-12-01)
Field: Materials Science — Biomaterials

Silk Polymers and Nanoparticles: A Powerful Combination for the Design of Versatile Biomaterials Silk fibroin (SF) is a natural protein largely used in the textile industry but also in biomedicine, catalysis, and other materials applications. SF is biocompatible, biodegradable, and possesses high tensile strength. Moreover, it is a versatile compound that can be formed into different materials at the macro, micro- and nano-scales, such as nanofibers, nanoparticles, hydrogels, microspheres, and other formats. Silk can be further integrated into emerging and promising additive manufacturing techniques like bioprinting, stereolithography or digital light processing 3D printing. As such, the development of methodologies for the functionalization of silk materials provide added value. Inorganic nanoparticles (INPs) have interesting and unexpected properties differing from bulk materials. These properties include better catalysis efficiency (better surface/volume ratio and consequently decreased quantify of catalyst), antibacterial activity, fluorescence properties, and UV-radiation protection or superparamagnetic behavior depending on the metal used. Given the promising results and performance of INPs, their use in many different procedures has been growing. Therefore, combining the useful properties of silk fibroin materials with those from INPs is increasingly relevant in many applications. Two main methodologies have been used in the literature to form silk-based bionanocomposites: <i>in situ</i> synthesis of INPs in silk materials, or the addition of preformed INPs to silk materials. This work presents an overview of current silk nanocomposites developed by these two main methodologies. An evaluation of overall INP characteristics and their distribution within the material is presented for each approach. Finally, an outlook is provided about the potential applications of these resultant nanocomposite materials. SILK ; Fibroin ; Materials science ; Nanotechnology ; Nanocomposite ; Stereolithography ; Nanofiber ; Nanoparticle ; Polymer ; Surface modification ; Chemical engineering ; Composite material Silk-based biomaterials and applications ; Bone Tissue Engineering Materials ; Electrospun Nanofibers in Biomedical Applications
Authors: Yuan-Chih Lin | Marco Bettinelli | Suchinder K. Sharma | Britta Redlich | Adolfo Speghini | Maths Karlsson
Source: Journal of Materials Chemistry C (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Unraveling the impact of different thermal quenching routes on the luminescence efficiency of the Y<sub>3</sub>Al<sub>5</sub>O<sub>12</sub>:Ce<sup>3+</sup>phosphor for white light emitting diodes Ratio of the radiative and nonradiative transition rates of YAG:Ce<sup>3+</sup>phosphor, affected by mode-selective vibrational excitation with an IR laser. Phosphor ; Luminescence ; Materials science ; Excitation ; Quenching (fluorescence) ; Analytical Chemistry (journal) ; Radiative transfer ; Atomic physics ; Laser ; Thermal ; Optoelectronics ; Optics ; Fluorescence ; Physics ; Chemistry ; Thermodynamics Luminescence Properties of Advanced Materials ; Radiation Detection and Scintillator Technologies ; Solid State Laser Technologies
Authors: Puneet Mishra | Jean‐Michel Roger | Douglas N. Rutledge | Alessandra Biancolillo | Federico Marini | Alison Nordon | Delphine Jouan‐Rimbaud Bouveresse
Source: Chemometrics and Intelligent Laboratory Systems (article, 2020-08-19)
Field: Chemistry — Analytical Chemistry

MBA-GUI: A chemometric graphical user interface for multi-block data visualisation, regression, classification, variable selection and automated pre-processing In recent years, due to advances in sensor technology, multi-modal measurement of process and products properties has become easier. However, multi-modal measurements are only of use if the data from adding new sensors is worthwhile, especially in the case of industrial applications where financial justification is needed for new sensor purchase and integration, and if the multi-modal data generated can be properly utilised. Several multi-block methods have been developed to do this; however, their use is largely limited to chemometricians, and non-experts have little experience with such methods. To deal with this, we present the first version of a MATLAB-based graphical user interface (GUI) for multi-block data analysis (MBA), capable of performing data visualisation, regression, classification and variable selection for up to 4 different sensors. The MBA-GUI can also be used to implement a recent technique called sequential pre-processing through orthogonalization (SPORT). Data sets are supplied to demonstrate how to use the MBA-GUI. In summary, the developed GUI makes the implementation of multi-block data analysis easier, so that it could be used also by practitioners with no programming skills or unfamiliar with the MATLAB environment. The fully functional GUI can be downloaded from (https://github.com/puneetmishra2/Multi-block.git) and can be either installed to run in the MATLAB environment or as a standalone executable program. The GUI can also be used for analysis of a single block of data (standard chemometrics). Executable ; Graphical user interface ; Computer science ; Block (permutation group theory) ; MATLAB ; Data mining ; Visualization ; Interface (matter) ; Data visualization ; Data processing ; Variable (mathematics) ; Database ; Programming language ; Operating system ; Mathematics Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Advanced Chemical Sensor Technologies
Authors: Saif Hannan | Mohammad Tariqul Islam | Norsuzlin Mohd Sahar | Kamarulzaman Mat | Muhammad E. H. Chowdhury | Hatem Rmili
Source: IEEE Access (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Modified-Segmented Split-Ring Based Polarization and Angle-Insensitive Multi-Band Metamaterial Absorber for X, Ku and K Band Applications A novel modified-segmented split-ring based symmetric metamaterial absorber is introduced in this paper for X, Ku, and K band applications. The perfect absorption was achieved with a total of 1.91 GHz absorption bandwidth using the conventional FR4 substrate without resistive lumped elements. EM waves were applied in TEM mode at both normal and oblique incidence up to 90° and the same absorptance was found at 11.23 GHz, 14.18 GHz, 17.37 GHz, and 19.18 GHz with the maximum of 85.51%, 99.13%, 98.19%, and 90.8% absorptance respectively. This absorption performance was proved for both co- and cross-polarization analysis. Double negative values of permittivity and permeability up to 17.37 GHz and single negative values of either permittivity or permeability at 19.18 GHz were achieved. An equivalent circuit analysis also proved its performance capability, which makes it a perfect metamaterial absorber. Finally, the comparison of the design with recently published works in terms of unit cell size, absorption band, maximum polarization angles, and cross-polarized absorptivity proved it as a better candidate for the potential use as a perfect absorber. Metamaterial ; Materials science ; Absorptance ; Metamaterial absorber ; Molar absorptivity ; Permittivity ; Optics ; Polarization (electrochemistry) ; Optoelectronics ; Physics ; Dielectric ; Tunable metamaterials ; Reflectivity Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Amgad R. Rezk | Heba Ahmed | Shwathy Ramesan | Leslie Y. Yeo
Source: Advanced Science (review, 2020-11-23)
Field: Materials Science — Materials Chemistry

High Frequency Sonoprocessing: A New Field of Cavitation‐Free Acoustic Materials Synthesis, Processing, and Manipulation Ultrasound constitutes a powerful means for materials processing. Similarly, a new field has emerged demonstrating the possibility for harnessing sound energy sources at considerably higher frequencies (10 MHz to 1 GHz) compared to conventional ultrasound (⩽3 MHz) for synthesizing and manipulating a variety of bulk, nanoscale, and biological materials. At these frequencies and the typical acoustic intensities employed, cavitation-which underpins most sonochemical or, more broadly, ultrasound-mediated processes-is largely absent, suggesting that altogether fundamentally different mechanisms are at play. Examples include the crystallization of novel morphologies or highly oriented structures; exfoliation of 2D quantum dots and nanosheets; polymer nanoparticle synthesis and encapsulation; and the possibility for manipulating the bandgap of 2D semiconducting materials or the lipid structure that makes up the cell membrane, the latter resulting in the ability to enhance intracellular molecular uptake. These fascinating examples reveal how the highly nonlinear electromechanical coupling associated with such high-frequency surface vibration gives rise to a variety of static and dynamic charge generation and transfer effects, in addition to molecular ordering, polarization, and assembly-remarkably, given the vast dimensional separation between the acoustic wavelength and characteristic molecular length scales, or between the MHz-order excitation frequencies and typical THz-order molecular vibration frequencies. Materials science ; Cavitation ; Acoustic wave ; Nanoscopic scale ; Nanotechnology ; Acoustic streaming ; Vibration ; Polarization (electrochemistry) ; Optoelectronics ; Excitation ; Acoustics ; Ultrasonic sensor ; Chemistry ; Physics Ultrasound and Cavitation Phenomena ; Nanopore and Nanochannel Transport Studies ; Microfluidic and Bio-sensing Technologies
Authors: U.T. Uthappa | O.R. Arvind | Ganesan Sriram | Dušan Lošić | Ho-Young-Jung | Madhuprasad Kigga | Mahaveer D. Kurkuri
Source: Journal of Drug Delivery Science and Technology (article, 2020-08-17)
Field: Materials Science — Materials Chemistry

Nanodiamonds and their surface modification strategies for drug delivery applications Nanotechnology ; Drug delivery ; Biocompatibility ; Nanomaterials ; Materials science ; Carbon nanotube ; Surface modification ; Fullerene ; Chemistry ; Organic chemistry Diamond and Carbon-based Materials Research ; Laser-Ablation Synthesis of Nanoparticles ; Graphene and Nanomaterials Applications
Authors: Kateřina Čubová | Václav Čuba
Source: Radiation Physics and Chemistry (review, 2020-02-22)
Field: Materials Science — Materials Chemistry

Synthesis of inorganic nanoparticles by ionizing radiation – a review Radiolysis ; Ionizing radiation ; Nanoparticle ; Nanomaterials ; Aqueous solution ; Irradiation ; Metal ; Chemistry ; Materials science ; Radiation chemistry ; Nanotechnology ; Chemical engineering ; Organic chemistry ; Chemical reaction Quantum Dots Synthesis And Properties ; Advanced Photocatalysis Techniques ; Luminescence Properties of Advanced Materials
Authors: Wei Qin | Jing Ma | Yusheng Zhou | Qin Hu | Yan Zhou | Guodong Liang
Source: Chemical Engineering Journal (article, 2020-06-17)
Field: Materials Science — Materials Chemistry

Simultaneous promotion of efficiency and lifetime of organic phosphorescence for self-referenced temperature sensing Phosphorescence ; Stacking ; Substituent ; Materials science ; Intermolecular force ; Phosphor ; Fluorine ; Photochemistry ; Optoelectronics ; Chemistry ; Organic chemistry ; Molecule ; Optics ; Fluorescence Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Perovskite Materials and Applications
Authors: Ying Pan | Qiongjie Ding | Baohong Li | Xiaoxiong Wang | Yiwei Liu | Junhao Chen | Fei Ke | Jianqiang Liu
Source: Chemosphere (article, 2020-09-01)
Field: Chemistry — Inorganic Chemistry

Self-adjusted bimetallic zeolitic-imidazolate framework-derived hierarchical magnetic carbon composites as efficient adsorbent for optimizing drug contaminant removal Zeolitic imidazolate framework ; Bimetallic strip ; Adsorption ; Imidazolate ; Materials science ; Carbon fibers ; Composite material ; Chemical engineering ; Metal-organic framework ; Chemistry ; Composite number ; Metal ; Metallurgy ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Adsorption and biosorption for pollutant removal ; Covalent Organic Framework Applications
Authors: Amvrosios G. Georgiadis | Nikolaos D. Charisiou | Ioannis V. Yentekakis | Maria A. Goula
Source: Materials (review, 2020-08-17)
Field: Chemistry — Inorganic Chemistry

Hydrogen Sulfide (H2S) Removal via MOFs The removal of the environmentally toxic and corrosive hydrogen sulfide (H<sub>2</sub>S) from gas streams with varying overall pressure and H<sub>2</sub>S concentration is a long-standing challenge faced by the oil and gas industries. The present work focuses on H<sub>2</sub>S capture using a relatively new type of material, namely metal-organic frameworks (MOFs), in an effort to shed light on their potential as adsorbents in the field of gas storage and separation. MOFs hold great promise as they make possible the design of structures from organic and inorganic units, but also as they have provided an answer to a long-term challenging objective, i.e., how to design extended structures of materials. Moreover, in designing MOFs, one may functionalize the organic units and thus, in essence, create pores with different functionalities, and also to expand the pores in order to increase pore openings. The work presented herein provides a detailed discussion, by thoroughly combining the existing literature on new developments in MOFs for H<sub>2</sub>S removal, and tries to provide insight into new areas for further research. Hydrogen sulfide ; Metal-organic framework ; Hydrogen sulphide ; Nanotechnology ; Materials science ; Fossil fuel ; Work (physics) ; Sulfide ; Adsorption ; Waste management ; Process engineering ; Environmental science ; Biochemical engineering ; Engineering ; Chemistry ; Mechanical engineering ; Sulfur ; Organic chemistry ; Metallurgy Metal-Organic Frameworks: Synthesis and Applications ; Industrial Gas Emission Control ; Sulfur Compounds in Biology
Authors: Johannes Martin | Christian Knüpfer | Jonathan Eyselein | Christian Färber | Samuel Grams | Jens Langer | Katharina Thum | Michael Wiesinger | Sjoerd Harder
Source: Angewandte Chemie International Edition (article, 2020-02-11)
Field: Chemistry — Inorganic Chemistry

Highly Active Superbulky Alkaline Earth Metal Amide Catalysts for Hydrogenation of Challenging Alkenes and Aromatic Rings Two series of bulky alkaline earth (Ae) metal amide complexes have been prepared: Ae[N(TRIP)<sub>2</sub> ]<sub>2</sub> (1-Ae) and Ae[N(TRIP)(DIPP)]<sub>2</sub> (2-Ae) (Ae=Mg, Ca, Sr, Ba; TRIP=SiiPr<sub>3</sub> , DIPP=2,6-diisopropylphenyl). While monomeric 1-Ca was already known, the new complexes have been structurally characterized. Monomers 1-Ae are highly linear while the monomers 2-Ae are slightly bent. The bulkier amide complexes 1-Ae are by far the most active catalysts in alkene hydrogenation with activities increasing from Mg to Ba. Catalyst 1-Ba can reduce internal alkenes like cyclohexene or 3-hexene and highly challenging substrates like 1-Me-cyclohexene or tetraphenylethylene. It is also active in arene hydrogenation reducing anthracene and naphthalene (even when substituted with an alkyl) as well as biphenyl. Benzene could be reduced to cyclohexane but full conversion was not reached. The first step in catalytic hydrogenation is formation of an (amide)AeH species, which can form larger aggregates. Increasing the bulk of the amide ligand decreases aggregate size but it is unclear what the true catalyst(s) is (are). DFT calculations suggest that amide bulk also has a noticeable influence on the thermodynamics for formation of the (amide)AeH species. Complex 1-Ba is currently the most powerful Ae metal hydrogenation catalyst. Due to tremendously increased activities in comparison to those of previously reported catalysts, the substrate scope in hydrogenation catalysis could be extended to challenging multi-substituted unactivated alkenes and even to arenes among which benzene. Amide ; Catalysis ; Alkaline earth metal ; Metal ; Chemistry ; Aromaticity ; Organic chemistry ; Molecule Asymmetric Hydrogenation and Catalysis ; Organoboron and organosilicon chemistry ; Catalysis and Hydrodesulfurization Studies