jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shiqi Guo | Dong Yang | Baichen Li | Quan Dong | Zhenyu Li | Mona Zaghloul
Source:  (article, 2019-08-01)
Field: Materials Science — Materials Chemistry

An Artificial Intelligent Flexible Gas Sensor Based on Ultra-Large Area MoSe<sub>2</sub> Nanosheet Flexible electronic applications based on transition metal dichalcogenides (TMDCs) nanosheet are extremely impressive recently. Synthesis of ultra-large area atomic layer molybdenum diselenide (MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) on a flexible substrate is the kernel of the fabrication process. In this work, we successfully transferred the ultra-large area of MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> atomic layer flakes on Kapton film with gold-mediated exfoliation method. The large area MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> nanosheet works as an active chemical gas sensing channel for flexible functional devices. The two terminal flexible gas sensor exhibited high responsivity under concentration for NH <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> and NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> of 5ppm and 1ppm, respectively. The flexible electronics were bent and further tested with an external circuit. In addition, an artificial intelligent data processing method with machine learning is applied to localize the toxic gas source. These results suggested that wearable large area MoSe <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> atomic layer is promising for wearable environmental detection applications. Nanosheet ; Materials science ; Computer science ; Nanotechnology 2D Materials and Applications ; Perovskite Materials and Applications ; Gas Sensing Nanomaterials and Sensors
Authors: Akhil Gopinath | Bharathi Ganesan Retnam | Arun Muthukkumaran | Kannan Aravamudan
Source: Journal of Molecular Liquids (article, 2019-10-23)
Field: Chemistry — Analytical Chemistry

Swift, versatile and a rigorous kinetic model based artificial neural network surrogate for single and multicomponent batch adsorption processes Ternary operation ; Biological system ; Artificial neural network ; Kinetics ; Diffusion ; Computer science ; Materials science ; Thermodynamics ; Artificial intelligence ; Physics Analytical chemistry methods development ; Analytical Chemistry and Chromatography ; Water Quality Monitoring and Analysis
Authors: Tibor Szilvási | Benjamin W. J. Chen | Manos Mavrikakis
Source: npj Computational Materials (article, 2019-10-25)
Field: Materials Science — Materials Chemistry

Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm Abstract The diverse coordination environments on the surfaces of discrete, three-dimensional (3D) nanoclusters contribute significantly to their unique catalytic properties. Identifying the numerous adsorption sites and diffusion paths on these clusters is however tedious and time-consuming, especially for large, asymmetric nanoclusters. Here, we present a simple, automated method for constructing approximate 2D potential energy surfaces for the adsorption of atomic species on the surfaces of 3D nanoclusters with minimal human intervention. These potential energy surfaces fully characterize the important adsorption sites and diffusion paths on the nanocluster surfaces with accuracies similar to current approaches and at comparable computational cost. Our method can treat complex nanoclusters, such as alloy nanoclusters, and accounts for cluster relaxation and adsorbate-induced reconstruction, important for obtaining accurate energetics. Moreover, its highly parallelizable nature is ideal for modern supercomputer architectures. We showcase our method using two clusters: Au 18 and Pt 55 . For Au 18 , diffusion of atomic hydrogen between the most stable sites occurs via non-intuitive paths, underlining the necessity of exploring the complete potential energy surface. By enabling the rapid and unbiased assessment of adsorption and diffusion on large, complex nanoclusters, which are particularly difficult to handle manually, our method will help advance materials discovery and the rational design of catalysts. Nanoclusters ; Adsorption ; Diffusion ; Cluster (spacecraft) ; Nanotechnology ; Materials science ; Surface diffusion ; Chemical physics ; Computer science ; Chemistry ; Physics ; Physical chemistry ; Thermodynamics Nanocluster Synthesis and Applications ; Machine Learning in Materials Science ; Catalytic Processes in Materials Science
Authors: Aleandro Antidormi | Stephan Roche | Luciano Colombo
Source: Journal of Physics Materials (article, 2019-12-04)
Field: Materials Science — Materials Chemistry

Impact of oxidation morphology on reduced graphene oxides upon thermal annealing Abstract Thermal reduction of graphene oxide (GO) is an essential technique to produce low-cost and higher quality graphene-based materials and composites used today in a plethora of applications. However, despite a demonstrated efficiency of high-temperature annealing in reducing the oxygen content of GO, the impact of the morphology of the initially oxidized samples on the restored sp 2 graphene plane versus remaining sp 3 imperfections remains unclear and out-of-control. Here using classical molecular dynamics, we simulate the process of thermal reduction on several GO samples for a variety of initial conditions and elucidate how both the concentration of oxygen functional groups and their spatial distribution jeopardize the reduction process efficiency. Our simulations suggest thermal annealing strategies to further optimize the crystallinity of reduced GO, enhancing their transport properties and hence making the resulting composites even more performant for electronic applications. Graphene ; Crystallinity ; Oxide ; Annealing (glass) ; Materials science ; Thermal ; Nanotechnology ; Chemical engineering ; Thermal oxidation ; Composite material ; Metallurgy ; Thermodynamics Graphene research and applications ; Advanced Memory and Neural Computing ; Semiconductor materials and devices
Authors: Ivano E. Castelli | Thomas Olsen | Yunzhong Chen
Source: Journal of Physics Energy (article, 2019-09-09)
Field: Materials Science — Materials Chemistry

Towards photoferroic materials by design: recent progress and perspectives Abstract The use of photoferroic materials that combine ferroelectric and light-harvesting properties in a photovoltaic device is a promising route to significantly improving the efficiency of solar cells. These materials do not require the formation of a p−n junction and can produce photovoltages well above the value of the band gap, because of spontaneous intrinsic polarization and the formation of domain walls. From this perspective, we discuss the recent experimental progress and challenges regarding the synthesis of these materials and the theoretical discovery of novel photoferroic materials using a high-throughput approach. Engineering ethics ; Management science ; Engineering 2D Materials and Applications ; Multiferroics and related materials ; Perovskite Materials and Applications
Authors: R. L. Mitchell | Mark Coleman | Peter Davies | Laura North | Edward C. Pope | Cameron Pleydell‐Pearce | Will Harris | Richard Johnston
Source: Journal of The Royal Society Interface (article, 2019-08-01)
Field: Materials Science — Biomaterials

Macro-to-nanoscale investigation of wall-plate joints in the acorn barnacle <i>Semibalanus balanoides</i> : correlative imaging, biological form and function, and bioinspiration Correlative imaging combines information from multiple modalities (physical-chemical-mechanical properties) at various length scales (centimetre to nanometre) to understand the complex biological materials across dimensions (2D-3D). Here, we have used numerous coupled systems: X-ray microscopy (XRM), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), optical light microscopy (LM) and focused ion beam (FIB-SEM) microscopy to ascertain the microstructural and crystallographic properties of the wall-plate joints in the barnacle Semibalanus balanoides. The exoskeleton is composed of six interlocking wall plates, and the interlocks between neighbouring plates (alae) allow barnacles to expand and grow while remaining sealed and structurally strong. Our results indicate that the ala contain functionally graded orientations and microstructures in their crystallography, which has implications for naturally functioning microstructures, potential natural strengthening and preferred oriented biomineralization. Elongated grains at the outer edge of the ala are oriented perpendicularly to the contact surface, and the c-axis rotates with the radius of the ala. Additionally, we identify for the first time three-dimensional nanoscale ala pore networks revealing that the pores are only visible at the tip of the ala and that pore thickening occurs on the inside (soft bodied) edge of the plates. The pore networks appear to have the same orientation as the oriented crystallography, and we deduce that the pore networks are probably organic channels and pockets, which are involved with the biomineralization process. Understanding these multiscale features contributes towards an understanding of the structural architecture in barnacles, but also their consideration for bioinspiration of human-made materials. The work demonstrates that correlative methods spanning different length scales, dimensions and modes enable the extension of the structure-property relationships in materials to form and function of organisms. Biomineralization ; Electron backscatter diffraction ; Materials science ; Microstructure ; Nanoscopic scale ; Focused ion beam ; Microscopy ; Scanning electron microscope ; Nanotechnology ; Composite material ; Optics ; Geology ; Chemistry ; Ion ; Physics Calcium Carbonate Crystallization and Inhibition ; Paleontology and Stratigraphy of Fossils ; Bone Tissue Engineering Materials
Authors: Suma Ayyagari | Marwan Al‐Haik
Source: Applied Sciences (article, 2019-06-03)
Field: Materials Science — Materials Chemistry

Enhancing the Viscoelastic Performance of Carbon Fiber Composites by Incorporating CNTs and ZnO Nanofillers Carbon fiber reinforced plastic composites (CFRPs) possess superior elastic mechanical properties. However, CFRPs lack sufficient viscoelastic performance, such as damping and creep resistance. In an effort to improve these properties, in this study, hybrid multiscale composites with various combinations of zinc oxide nanorods (ZnO) and carbon nanotubes (CNTs) were deposited at the interface of carbon fiber laminae. The viscoelastic properties of the corresponding composites were characterized via dynamic mechanical analysis (DMA) during both temperature and frequency sweeps. The creep activation energy for each composite configuration was also calculated. The DMA temperature sweep analysis reported that the composite incorporating both ZnO and CNTs exhibited the highest improvements in all viscoelastic properties. This composite also attained better creep resistance, evident by the highest activation energy. The DMA frequency sweep analysis revealed that composites incorporating a single nanofiller improves the viscoelastic properties more than the combined nanofiller composite. Despite these improvements in the viscoelastic properties, the non-uniform dispersion and agglomerations of the nanofillers affected some of the elastic properties negatively, such as the storage modulus. Materials science ; Viscoelasticity ; Composite material ; Creep ; Dynamic mechanical analysis ; Carbon nanotube ; Composite number ; Dynamic modulus ; Polymer Carbon Nanotubes in Composites ; Smart Materials for Construction ; Tribology and Wear Analysis
Authors: Minttu M. Kauppinen | Ville Korpelin | Anand Mohan Verma | Marko Melander | Karoliina Honkala
Source: The Journal of Chemical Physics (article, 2019-10-22)
Field: Materials Science — Materials Chemistry

Escaping scaling relationships for water dissociation at interfacial sites of zirconia-supported Rh and Pt clusters Water dissociation is an important reaction involved in many industrial processes. In this computational study, the dissociation of water is used as a model reaction for probing the activity of interfacial sites of globally optimized ZrO<sub>2</sub> supported Pt and Rh clusters under the framework of density functional theory. Our findings demonstrate that the perimeter sites of these small clusters can activate water, but the dissociation behavior varies considerably between sites. It is shown that the studied clusters break scaling relationships for water dissociation, suggesting that these catalysts may achieve activities beyond the maximum imposed by such relations. Furthermore, we observed large differences in the thermodynamics of the water dissociation reaction between global minimum and near-global minimum isomers of the clusters. Overall, our results highlight the uniqueness of interfacial sites in catalytic reactions and the need for developing new concepts and tools to deal with the associated complexity. Dissociation (chemistry) ; Scaling ; Catalysis ; Uniqueness ; Chemical physics ; Chemistry ; Self-ionization of water ; Density functional theory ; Physical chemistry ; Computational chemistry ; Mathematics ; Geometry ; Organic chemistry Catalytic Processes in Materials Science ; Theoretical and Computational Physics ; Electrocatalysts for Energy Conversion
Authors: Hilario Martines-Arano | Blanca Estela Garcı́a-Pérez | Mónica Araceli Vidales-Hurtado | M. Trejo-Valdéz | Luis Héctor Hernández-Gómez | C. Torres-Torres
Source: Sensors (article, 2019-10-31)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Chaotic Signatures Exhibited by Plasmonic Effects in Au Nanoparticles with Cells The evolution of the optical absorptive effects exhibited by plasmonic nanoparticles was systematically analyzed by electronic signals modulated by a Rössler attractor system. A sol-gel approach was employed for the preparation of the studied Au nanoparticles embedded in a TiO<sub>2</sub> thin solid film. The inclusion of the nanoparticles in an inhomogeneous biological sample integrated by human cells deposited in an ITO glass substrate was evaluated with a high level of sensitivity using an opto-electronic chaotic circuit. The optical response of the nanoparticles was determined using nanosecond laser pulses in order to guarantee the sensing performance of the system. It was shown that high-intensity irradiances at a wavelength of 532 nm could promote a change in the absorption band of the localized surface plasmon resonance associated with an increase in the nanoparticle density of the film. Moreover, it was revealed that interferometrically-controlled energy transfer mechanisms can be useful for thermo-plasmonic functions and sharp selective optical damage induced by the vectorial nature of light. Immediate applications of two-wave mixing techniques, together with chaotic effects, can be contemplated in the development of nanostructured sensors and laser-induced controlled explosions, with potential applications for biomedical photo-thermal processes. Materials science ; Nanoparticle ; Plasmon ; Laser ; Optoelectronics ; Nanotechnology ; Plasmonic nanoparticles ; Substrate (aquarium) ; Absorption (acoustics) ; Photothermal therapy ; Thin film ; Surface plasmon resonance ; Optics ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Circadian rhythm and melatonin ; Plasmonic and Surface Plasmon Research
Authors: Melek Ahmed | Glenn Broeckx | Geert Baggerman | Karin Schildermans | Patrick Pauwels | Amaryllis H. Van Craenenbroeck | Amélie Dendooven
Source: Journal of Clinical Pathology (review, 2019-07-15)
Field: Chemistry — Spectroscopy

Next-generation protein analysis in the pathology department Traditionally, immunohistochemistry (IHC) is used by pathologists to localise specific proteins or peptides in tissue slides. In the era of personalised medicine, however, molecular tissue analysis becomes indispensable for correct diagnosis, prognosis and therapeutic decision, not only on the DNA or mRNA level but also on the protein level. Combining molecular information with imaging presents many advantages. Therefore, matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI IMS) is a promising technique to be added to the armamentarium of the pathologist. Here, we focus on the workflow, advantages and drawbacks of both MALDI IMS and IHC. We also briefly discuss a few other protein imaging modalities and give examples of applications. MALDI imaging ; Immunohistochemistry ; Mass spectrometry imaging ; Pathology ; Workflow ; Modalities ; Molecular pathology ; Medicine ; Molecular imaging ; Computer science ; Focus (optics) ; Computational biology ; Medical physics ; Bioinformatics ; Matrix-assisted laser desorption/ionization ; Mass spectrometry ; Chemistry ; Biology ; Biochemistry ; Database ; Desorption ; Physics Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Molecular Biology Techniques and Applications
Authors: Vitalii Lozovan | Р. М. Джала | Ruslan Skrynkovskyy | Volodymyr Yuzevych
Source: Eastern-European Journal of Enterprise Technologies (article, 2019-01-23)
Field: Materials Science — Materials Chemistry

Detection of specific features in the functioning of a system for the anti-corrosion protection of underground pipelines at oil and gas enterprises using neural networks The information was reviewed to orderly arrange theoretical provisions and to devise practical recommendations for the diagnostic examination of a system for the anti-corrosion protection of underground metal oil and gas pipelines.A set of informative parameters for modeling functional relations and determining polarization potential in the system "underground metal structure – cathodic protection plant" was formed.It was proposed to apply the algorithm of prediction of corrosive current, the approach of non-linear programming, as well as the neural network, including the corresponding methods of learning, for a pipeline section, taking into account the polarization potential on the outer surface. The test set to evaluate the effectiveness of a neural network was formed.The above-mentioned information is essential for the improvement of the equipment of distant control of metal structures of oil and gas enterprises, that is, the procedures for correct measuring and evaluating direct and alternating voltages, as well as polarization potential in a pipeline.The methods and algorithms of neural networks, which are used to control the anticorrosive protection of underground pipelines, were explored. The study of the effectiveness of artificial neural networks, specifically, a two-layer network of direct propagation with the function of prediction of the resource of metal pipes. Using the polarization potential, we detected the capability of neural networks to perform inaccessible for conventional mathematics operations of processing, comparison, classification of images, capability of self-learning and self-organization relative to underground pipelines. The qualimetric quality criterion for a pipeline section, taking into consideration the optimal range of polarization potential was improved.We developed the method for prediction of the polarization potential of a cathodic protection plant and transitional specific resistance of the insulating coating on the surface of an underground metal structure using a neural network. Taking into consideration the results of analysis of polarization potential and transitional specific resistance, the methodology of formation of information support for procedures of degradation of anticorrosive dielectric coating and metal on the outer surface of an underground metal structure, as well as for predicting its resource, was designed Artificial neural network ; Pipeline transport ; Cathodic protection ; Polarization (electrochemistry) ; Corrosion ; Computer science ; Artificial intelligence ; Engineering ; Petroleum engineering ; Mechanical engineering ; Anode ; Materials science Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Industrial Engineering and Technologies
Authors: Douglas Franz | Jonathan L. Belof | Keith McLaughlin | Christian R. Cioce | Brant Tudor | Adam Hogan | Luciano Enrique Laratelli | Meagan Mulcair | Matthew Mostrom | Alejandro Navas | Abraham C. Stern | Katherine A. Forrest | Tony Pham | Brian Space
Source: Advanced Theory and Simulations (article, 2019-08-06)
Field: Chemistry — Spectroscopy

MPMC and MCMD: Free High‐Performance Simulation Software for Atomistic Systems Abstract Advancements in parallel computing and hardware have allowed computational exploration of chemical systems of interest with unprecendented accuracy and efficiency. The typical development of molecular simulation software is initially inspired by a particular scientific inquiry. The softwares presented herein, MPMC (Massively Parallel Monte Carlo) and MCMD (Monte Carlo/Molecular Dynamics) were born out of a pursuit to simulate condensed phase physical and chemical interactions in porous materials. MPMC first began in 2005 and has been used for dozens of published results in the literature but has not yet been introduced in a standalone paper. MCMD is a more recent expansion and re‐write with some published work, focused on adding molecular dynamics algorithms for transport and other time‐dependent properties of chemical systems. Each software functions as a standalone with some unique and other overlapping features. A driving aim of this work is to consider periodic, long‐range polarization effects in classical simulation, and both codes are optimized to perform such calculations. Sample results will be presented which highlight methodically that inclusion of explicit polarization produces simulation results with predictive power which in general are in greater agreement with experiment than non‐polarizable analogous simulations. Massively parallel ; Computer science ; Monte Carlo method ; Software ; Molecular dynamics ; Computational science ; Supercomputer ; Polarizability ; Statistical physics ; Complex system ; Parallel computing ; Physics ; Artificial intelligence ; Computational chemistry ; Chemistry Advanced NMR Techniques and Applications ; Machine Learning in Materials Science ; Advanced Chemical Physics Studies