jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: S. Joseph Poon
Source: Metals (article, 2018-11-24)
Field: Materials Science — Materials Chemistry

Recent Advances in Thermoelectric Performance of Half-Heusler Compounds Half-Heusler phases (space group F 4 ¯ 3 m , C1b) have recently captured much attention as promising thermoelectric materials for heat-to-electric power conversion in the mid-to-high temperature range. The most studied ones are the RNiSn-type half-Heusler compounds, where R represents refractory metals Hf, Zr, and Ti. These compounds have shown a high-power factor and high-power density, as well as good material stability and scalability. Due to their high thermal conductivity, however, the dimensionless figure of merit (zT) of these materials has stagnated near 1 for a long time. Since 2013, the verifiable zT of half-Heusler compounds has risen from 1 to near 1.5 for both n- and p-type compounds in the temperature range of 500–900 °C. In this brief review, we summarize recent advances as well as approaches in achieving the high zT reported. In particular, we discuss the less-exploited strain-relief effect and dopant resonant state effect studied by the author and his collaborators in more detail. Finally, we point out directions for further development. Thermoelectric materials ; Thermoelectric effect ; Figure of merit ; Dopant ; Thermal stability ; Refractory metals ; Solid-state ; Refractory (planetary science) Advanced Thermoelectric Materials and Devices ; Heusler alloys: electronic and magnetic properties ; 2D Materials and Applications
Authors: Na Lv | Xiaoli Wang | Shitao Peng | Huaqin Zhang | Lei Luo
Source: International Journal of Environmental Research and Public Health (article, 2018-05-12)
Field: Materials Science — Surfaces, Coatings and Films

Study of the Kinetics and Equilibrium of the Adsorption of Oils onto Hydrophobic Jute Fiber Modified via the Sol-Gel Method A new kind of hydrophobic and oil sorbent based on jute fiber was successfully prepared by the integration of silica onto a fiber surface via the sol-gel method and subsequent hydrophobic modification with octadecyltrichlorosilane (OTS). Compared with the hydrophilic raw fiber, the modified fiber had a water contact angle (CA) of 136.2&deg;, suggesting that the material has good hydrophobicity. Furthermore, the ability of oil in the oil/water system (taking diesel for example) to absorb was revealed by the kinetics, the isotherm equation, and the thermodynamic parameters. Adsorption behavior was kinetically investigated using pseudo first-order and pseudo second-order models. The data mostly correlated with the pseudo first-order model. The equilibrium adsorption at 298 K was assessed by using the Langmuir and Freundlich isotherm models. The Freundlich model had greater consistency with the experimental data. The obtained thermodynamic parameters demonstrate that the adsorption of diesel is spontaneous, favorable, and exothermic. Adsorption ; Freundlich equation ; Contact angle ; Fiber ; Octadecyltrichlorosilane ; Chemical engineering ; Sorbent ; Langmuir ; Materials science ; Kinetics ; Chemistry ; Organic chemistry ; Composite material Surface Modification and Superhydrophobicity ; Pickering emulsions and particle stabilization ; Hydrogels: synthesis, properties, applications
Authors: Giuseppina Anna Corrente | Eduardo Fabiano | Francesca Manni | G. Chidichimo | Giuseppe Gigli | Amerigo Beneduci | Agostina Lina Capodilupo
Source: Chemistry of Materials (article, 2018-07-30)
Field: Materials Science — Polymers and Plastics

Colorless to All-Black Full-NIR High-Contrast Switching in Solid Electrochromic Films Prepared with Organic Mixed Valence Systems Based on Dibenzofulvene Derivatives Functional electrochromic materials that allow energy modulation both in the visible and in the near-infrared (NIR) spectral ranges are attracting increasing interest both for the fundamental scientific aspects related to their spectroelectrochemistry and for their technological applications. Vis-NIR dimmable windows based on these materials are very promising for tunable shading, thus allowing lighting and heat energy use saving. Organic mixed valence compounds (MVs) are an interesting class of small molecules with NIR electrochromism arising from optically induced intervalence charge transfer transitions (IVCT). Here, we report the synthesis and vis-NIR electrochromic properties of new organic mixed valence systems, with two and three amino redox centers bridged by a dibenzofulvene (DBF) unit. We studied the neutral and charged state characteristics of these MVs in solution by spectroelectrochemical experiments, theoretical TD-DFT investigations, and, in the solid state, through electrochromic devices (ECDs). We show that a fine-tuning of the electro-optical properties of these MVs can be obtained by different functionalization on the exocyclic fulvene bond of the DBF moiety, including the introduction of a third redox center, leading to compounds where all three redox centers participate in the electron transfer processes as a function of the applied voltage. As a proof-of-concept, the above MVs were used to form solid thermoplastic laminable films in order to fabricate transmissive-to-black switching electrochromic devices, with intermediate color switching characteristics, enabling us to cover all the color palette. Beyond this important exploitability in the vis region, useful in many applications, the most important characteristic of these devices is their absorption in almost the whole NIR range (800–2200 nm) through the excitation of highly charged radical species, which show intense IVCTs. Importantly, all the devices show high optical contrast, response times of a few seconds, and excellent switching stability over 10 000 cycles. Electrochromism ; Valence (chemistry) ; Materials science ; Electrochromic devices ; Redox ; Optoelectronics ; Photochemistry ; Chemistry ; Electrode ; Organic chemistry ; Physical chemistry Conducting polymers and applications ; Transition Metal Oxide Nanomaterials ; Perovskite Materials and Applications
Authors: Kévin Robert | Camille Douard | Arnaud Demortière | Florent Blanchard | Pascal Roussel | Thierry Brousse | Christophe Lethien
Source: Advanced Materials Technologies (article, 2018-06-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

On Chip Interdigitated Micro‐Supercapacitors Based on Sputtered Bifunctional Vanadium Nitride Thin Films with Finely Tuned Inter‐ and Intracolumnar Porosities Abstract Micro‐supercapacitors (MSC) are considered as promising miniaturized electrochemical energy storage devices for Internet of Things applications. Unfortunately, the technological readiness level of these devices is still at the lab scale with the development of individual prototypes due to the difficulty to produce high performance porous electrode material with microelectronic equipment available in pilot production lines. Here, the collective fabrication of on chip MSC based on sputtered porous vanadium nitride (VN) bifunctional material is reported. For the first time in the field of MSC, the porosity of the sputtered VN thin films is fine‐tuned at the nanoscale level in order to produce high capacitance and high conductive electrodes. Interdigitated MSC based on optimized VN thin films are fabricated on silicon wafers using microelectronic facilities. 2 μWh cm −2 /10 mWh cm −3 energy densities are reached while keeping a high power density (10 mW cm −2 /&gt;50 W cm −3 ) owing to high electrical conductivity of VN layers. Sputtered vanadium nitride thin films are demonstrated to be suitable pseudocapacitive electrodes and highly conductive current collectors for MSC applications. These findings represent a major advance in order to go toward the large‐scale deployment of such miniaturized power sources. Vanadium nitride ; Supercapacitor ; Materials science ; Bifunctional ; Optoelectronics ; Vanadium ; Nitride ; Nanotechnology ; Thin film ; Chip ; Electrical engineering ; Metallurgy ; Capacitance ; Electrode ; Chemistry ; Engineering ; Layer (electronics) Supercapacitor Materials and Fabrication ; MXene and MAX Phase Materials ; Electrocatalysts for Energy Conversion
Authors: Gang Li | Ki‐Young Yoon | Xinjue Zhong | Jianchun Wang | Rui Zhang | Jeffrey R. Guest | Jianguo Wen | Xiaoyang Zhu | Guangbin Dong
Source: Nature Communications (article, 2018-04-23)
Field: Materials Science — Materials Chemistry

A modular synthetic approach for band-gap engineering of armchair graphene nanoribbons Despite the great promise of armchair graphene nanoribbons (aGNRs) as high-performance semiconductors, practical band-gap engineering of aGNRs remains an unmet challenge. Given that width and edge structures are the two key factors for modulating band-gaps of aGNRs, a reliable synthetic method that allows control of both factors would be highly desirable. Here we report a simple modular strategy for efficient preparation of N = 6 aGNR, the narrowest member in the N = 3p (p: natural number) aGNR family, and two unsymmetrically edge-functionalized GNRs that contain benzothiadiazole and benzotriazole moieties. The trend of band-gap transitions among these GNRs parallels those in donor-acceptor alternating conjugated polymers. In addition, post-functionalization of the unsymmetrical heterocyclic edge via C-H borylation permits further band-gap tuning. Therefore, this method opens the door for convenient band-gap engineering of aGNRs through modifying the heteroarenes on the edge. Graphene nanoribbons ; Band gap ; Materials science ; Enhanced Data Rates for GSM Evolution ; Nanotechnology ; Modular design ; Graphene ; Optoelectronics ; Computer science ; Telecommunications Graphene research and applications ; 2D Materials and Applications ; Synthesis and Properties of Aromatic Compounds
Authors: Manuel Le Gallo | Daniel Krebs | Federico Zipoli | Martin Salinga | Abu Sebastian
Source: Advanced Electronic Materials (article, 2018-07-16)
Field: Materials Science — Materials Chemistry

Collective Structural Relaxation in Phase‐Change Memory Devices Abstract Phase‐change memory devices are expected to play a key role in future computing systems as both memory and computing elements. A key challenge in this respect is the temporal evolution of the resistance levels commonly referred to as “resistance drift.” In this paper, a comprehensive description of resistance drift as a result of spontaneous structural relaxation of the amorphous phase‐change material toward an energetically more favorable ideal glass state is presented. Molecular dynamics simulations provide insights into the microscopic origin of the structural relaxation. Based on those insights, a collective relaxation model is proposed to capture the kinetics of structural relaxation. By linking the physical material parameters governing electrical transport to such a description of structural relaxation, an integrated drift model that is able to predict the current–voltage characteristics at any instance in time even during nontrivial temperature treatments is obtained. Accurate quantitative matching with experimental drift measurements over a wide range of time (10 decades) and temperature (160–420 K) is demonstrated. Relaxation (psychology) ; Materials science ; Amorphous solid ; Phase-change memory ; Matching (statistics) ; Phase (matter) ; Condensed matter physics ; Chemical physics ; Statistical physics ; Phase change ; Nanotechnology ; Engineering physics ; Physics ; Chemistry ; Crystallography Phase-change materials and chalcogenides ; Liquid Crystal Research Advancements ; Material Dynamics and Properties
Authors: Peter Bjørn Jørgensen | Mikkel N. Schmidt | Ole Winther
Source: Molecular Informatics (review, 2018-01-01)
Field: Materials Science — Materials Chemistry

Deep Generative Models for Molecular Science Generative deep machine learning models now rival traditional quantum-mechanical computations in predicting properties of new structures, and they come with a significantly lower computational cost, opening new avenues in computational molecular science. In the last few years, a variety of deep generative models have been proposed for modeling molecules, which differ in both their model structure and choice of input features. We review these recent advances within deep generative models for predicting molecular properties, with particular focus on models based on the probabilistic autoencoder (or variational autoencoder, VAE) approach in which the molecular structure is embedded in a latent vector space from which its properties can be predicted and its structure can be restored. Autoencoder ; Generative grammar ; Artificial intelligence ; Computer science ; Generative model ; Deep learning ; Machine learning ; Probabilistic logic ; Computational model Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Peng Liu | Jing Wang | Qian Li | Jun Gao | Xiaoyao Tan | Xihui Bian
Source: Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (article, 2018-08-01)
Field: Chemistry — Analytical Chemistry

Rapid identification and quantification of Panax notoginseng with its adulterants by near infrared spectroscopy combined with chemometrics Partial least squares regression ; Chemometrics ; Artificial intelligence ; Support vector machine ; Pattern recognition (psychology) ; Principal component analysis ; Linear discriminant analysis ; Mathematics ; Calibration ; Extreme learning machine ; Chromatography ; Chemistry ; Computer science ; Artificial neural network ; Statistics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Traditional Chinese Medicine Analysis
Authors: Viktoriia V. Torbina | Andrei A. Vodyankin | Sergey Ten | G. V. Mamontov | M.A. Salaev | В. И. Соболев | O. V. Vodyankina
Source: Catalysts (review, 2018-10-11)
Field: Materials Science — Materials Chemistry

Ag-Based Catalysts in Heterogeneous Selective Oxidation of Alcohols: A Review Alcohols (bioalcohols) is a class of chemicals that are used as a feedstock for the manufacturing of a large number of valuable intermediates in industrially important processes. Currently, sustainable technologies for selective conversion of alcohols utilize “green” oxidants, mainly, ambient air or oxygen. Due to the high affinity of oxygen towards silver, the latter serves as an active component of supported heterogeneous catalysts. In this review, we consider Ag-based catalysts that participate in gas- or liquid-phase oxidation of alcohols. Oxidation of methanol, ethanol, ethylene glycol, propylene glycol, glycerol, benzyl and allyl alcohols is mostly considered. A particular attention is paid to selective photooxidation of alcohols over Ag-based catalysts. We discuss the catalyst composition in terms of (1) the state of the active component, (2) the nature of the substrate, (3) support nature, and (4) the strength of the metal–support interactions. Catalysis ; Alcohol oxidation ; Chemistry ; Ethylene glycol ; Methanol ; Raw material ; Glycerol ; Organic chemistry ; Heterogeneous catalysis Catalytic Processes in Materials Science ; Oxidative Organic Chemistry Reactions ; Catalysis and Oxidation Reactions
Authors: Andrew D. McEachran | Kamel Mansouri | Chris Grulke | Emma Schymanski | Christoph Ruttkies | Antony Williams
Source: Journal of Cheminformatics (article, 2018-08-30)
Field: Chemistry — Spectroscopy

“MS-Ready” structures for non-targeted high-resolution mass spectrometry screening studies Chemical database searching has become a fixture in many non-targeted identification workflows based on high-resolution mass spectrometry (HRMS). However, the form of a chemical structure observed in HRMS does not always match the form stored in a database (e.g., the neutral form versus a salt; one component of a mixture rather than the mixture form used in a consumer product). Linking the form of a structure observed via HRMS to its related form(s) within a database will enable the return of all relevant variants of a structure, as well as the related metadata, in a single query. A Konstanz Information Miner (KNIME) workflow has been developed to produce structural representations observed using HRMS ("MS-Ready structures") and links them to those stored in a database. These MS-Ready structures, and associated mappings to the full chemical representations, are surfaced via the US EPA's Chemistry Dashboard ( https://comptox.epa.gov/dashboard/ ). This article describes the workflow for the generation and linking of ~ 700,000 MS-Ready structures (derived from ~ 760,000 original structures) as well as download, search and export capabilities to serve structure identification using HRMS. The importance of this form of structural representation for HRMS is demonstrated with several examples, including integration with the in silico fragmentation software application MetFrag. The structures, search, download and export functionality are all available through the CompTox Chemistry Dashboard, while the MetFrag implementation can be viewed at https://msbi.ipb-halle.de/MetFragBeta/ . Workflow ; Computer science ; Database ; Chemical database ; Cheminformatics ; Dashboard ; Identification (biology) ; Metadata ; Software ; Information retrieval ; Data mining ; Chemistry ; World Wide Web ; Programming language Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Shyqyri Haxha | F. AbdelMalek | F. Ouerghi | Martin D. B. Charlton | A. Aggoun | Fang Xu
Source: Scientific Reports (article, 2018-10-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metamaterial Superlenses Operating at Visible Wavelength for Imaging Applications In this paper, a novel design for a metamaterial lens (superlens) based on a Photonic Crystal (PC) operating at visible wavelengths is reported. The proposed superlens consist of a gallium phosphide (GaP) dielectric slab waveguide with a hexagonal array of silver rods embedded within the GaP dielectric. In-house 2DFDTD numerical method is used to design and optimize the proposed superlens. Several superlenses are designed and integrated within a same dielectric platform, promoting the proof-of-concept (POC) of possible construction of an array of superlenses (or sub-lenses to create an M-Lens) for light field imaging applications. It is shown that the concavity of the superlens and positioning of each sub-lens within the array strongly affects the performances of the image in terms of resolution. Defects and various geometrical shapes are introduced to construct and optimize the proposed superlenses and increase the quality of the image resolution. It is shown that the orientation of the active region (ellipse) along x and y axis has tremendous influence on the quality of image resolution. In order to investigate the performance characteristics of the superlenses, transmitted power is calculated using 2D FDTD for image projections at various distances (in x and y plane). It is also shown, how the proposed superlens structures could be fabricated using standard micro fabrication techniques such as electron beam lithography, inductively coupled Reactive ion etching, and glancing angle evaporation methods. To the best of our knowledge, these are the first reported POC of superlenses, integrated in a monolithic platform suitable for high imaging resolution that can be used for light field imaging applications at visible wavelength. The proposed superlenses (integrated in a single platform M-Lens) will have tremendous impact on imaging applications. Superlens ; Optics ; Metamaterial ; Materials science ; Lens (geology) ; Image quality ; Dielectric ; Optoelectronics ; Photonic crystal ; Negative refraction ; Computer science ; Physics Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Advanced Antenna and Metasurface Technologies
Authors: Xin‐Feng Wei | Loris De Vico | Pierre Larroche | Kai J. Kallio | Stefan Bruder | Martin Bellander | Ulf W. Gedde | Mikael S. Hedenqvist
Source: npj Materials Degradation (article, 2018-12-27)
Field: Materials Science — Biomaterials

Ageing properties and polymer/fuel interactions of polyamide 12 exposed to (bio)diesel at high temperature Abstract Biodiesel derived from oil crops and animal fats has been developed as a promising carbon-neutral alternative to petroleum fuels in the transport sector, but the compatibility between biodiesel/petroleum diesel and polymer components in the automotive fuel system has not been free from controversy. In this present study, the degradation of polyamide 12 (PA12), one of the most common polymers used in vehicle fuel systems, has been investigated after exposure to petroleum diesel, biodiesel and a mixture of these (20 vol.% of biodiesel/80 vol.% petroleum diesel). Fuel sorption kinetics, glass transition temperature data and mechanical properties all showed that the fuels plasticized the PA12. In addition, monomers and oligomers were extracted from PA12 by the fuels. The long-term exposure led to oxidation and an annealing-induced increase in crystallinity of the polymer. The plasticization, oxidation and annealing effects were combined with the tensile mechanical properties to assess the overall degree of ageing and degradation of the PA12 material. The fuel-polymer interactions and ageing mechanisms, demonstrated here at high temperature for PA12, are 'generic' in the sense that they are also expected to occur, to various degrees, with many other polymers and they indicate that care should be taken when choosing polymers in applications where they will be exposed to fuels at high temperature. Diesel fuel ; Biodiesel ; Materials science ; Polymer ; Petroleum ; Chemical engineering ; Plasticizer ; Polyamide ; Composite material ; Organic chemistry ; Chemistry ; Catalysis biodegradable polymer synthesis and properties ; Polymer crystallization and properties ; Biodiesel Production and Applications
Authors: Benjamín Sánchez-Lengeling | Loı̈c M. Roch | José Darío Perea | Stefan Langner | Christoph J. Brabec | Alán Aspuru‐Guzik
Source: Advanced Theory and Simulations (article, 2018-09-10)
Field: Materials Science — Materials Chemistry

A Bayesian Approach to Predict Solubility Parameters Abstract Solubility is a ubiquitous phenomenon in many aspects of material science. While solubility can be determined by considering the cohesive forces in a liquid via the Hansen solubility parameters (HSP), quantitative structure–property relationship models are often used for prediction, notably due to their low computational cost. Here, gpHSP, an interpretable and versatile probabilistic approach to determining HSP, is reported. Our model is based on Gaussian processes, a Bayesian machine learning approach that provides uncertainty bounds to prediction. gpHSP achieves its flexibility by leveraging a variety of input data, such as SMILES strings, COSMOtherm simulations, and quantum chemistry calculations. gpHSP is built on experimentally determined HSP, including a general solvents set aggregated from the literature, and a polymer set experimentally characterized by this group of authors. In all sets, a high degree of agreement is obtained, surpassing well‐established machine learning methods. The general applicability of gpHSP to miscibility of organic semiconductors, drug compounds, and in general solvents is demonstrated, which can be further extended to other domains. gpHSP is a fast and accurate toolbox, which could be applied to molecular design for solution processing technologies. Solubility ; Bayesian probability ; Miscibility ; Computer science ; Flexibility (engineering) ; Probabilistic logic ; Set (abstract data type) ; Toolbox ; Consistency (knowledge bases) ; Biological system ; Algorithm ; Chemistry ; Artificial intelligence ; Polymer ; Statistical physics ; Mathematics ; Physics ; Organic chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Crystallization and Solubility Studies