jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sergey V. Levchenko | Yaqiong Zhong | Xiaojuan Hu | Debalaya Sarker | Qingrui Xia | Liangliang Xu | Chao Yang | Zhongkang Han | Jiaolin Cui
Source: Research Square (preprint, 2021-10-04)
Field: Materials Science — Materials Chemistry

Data analytics accelerates the experimental discovery of new thermoelectric materials with extremely high figure of merit Abstract Thermoelectric (TE) materials are among very few sustainable yet feasible energy solutions of present time. This huge promise of energy harvesting is contingent on identifying/designing materials having higher efficiency than presently available ones. However, due to the vastness of the chemical space of materials, only its small fraction was scanned experimentally and/or computationally so far. Employing a compressed-sensing based symbolic regression in an active-learning framework, we have not only identified a trend in materials’ compositions for superior TE performance, but have also predicted and experimentally synthesized several extremely high performing novel TE materials. Among these, we found polycrystalline p-type Cu 0.45 Ag 0.55 GaTe 2 to possess an experimental figure of merit as high as ~2.8 at 827 K. This is a breakthrough in the field, because all previously known thermoelectric materials with a comparable figure of merit are either unstable or much more difficult to synthesize, rendering them unusable in large-scale applications. The presented methodology demonstrates the importance and tremendous potential of physically informed descriptors in material science, in particular for relatively small data sets typically available from experiments at well-controlled conditions. Figure of merit ; Analytics ; Data science ; Thermoelectric effect ; Computer science ; Materials science ; Engineering physics ; Engineering ; Physics ; Optoelectronics ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Chalcogenide Semiconductor Thin Films ; Thermal Radiation and Cooling Technologies
Authors: Lukas Turcani | Andrew Tarzia | Filip Szczypiński | Kim E. Jelfs
Source: ChemRxiv (preprint, 2021-03-09)
Field: Materials Science — Materials Chemistry

Stk: An Extendable Python Framework for Automated Molecular and Supramolecular Structure Assembly and Discovery &lt;div&gt;Computational software workflows are emerging as all-in-one solutions to speed up the discovery of new materials.&lt;/div&gt;&lt;div&gt;Many computational approaches require the generation of realistic structural models for property prediction and candidate screening. However, molecular and supramolecular materials represent classes of materials with many potential applications for which there is no go-to database of existing structures or general protocol for generating structures. Here, we report a new version of the supramolecular toolkit, &lt;i&gt;stk&lt;/i&gt;, an open-source, extendable and modular Python framework for general structure generation of (supra)molecular structures. Our construction approach follows a bottom-up process and minimises the input required from the user, making &lt;i&gt;stk&lt;/i&gt; user-friendly and applicable to many material classes. This version of &lt;i&gt;stk&lt;/i&gt; includes metal-containing structures and rotaxanes as well as general implementation and interface improvements. Additionally, this version includes built-in tools for exploring chemical space with an evolutionary algorithm and tools for database generation and visualisation. The latest version of &lt;i&gt;stk&lt;/i&gt; is freely available at github.com/lukasturcani/stk&lt;/div&gt; Python (programming language) ; Workflow ; Computer science ; Modular design ; Supramolecular chemistry ; Software ; Computational science ; Programming language ; Computational biology ; Chemistry ; Database ; Biology ; Crystallography Machine Learning in Materials Science ; Surface Chemistry and Catalysis ; Catalysis and Oxidation Reactions
Authors: AmirHossein Foroozan-Ebrahimy | Brian Langelier | Roger Newman
Source: Nanomaterials (article, 2021-04-14)
Field: Materials Science — Materials Chemistry

Probing the Surface Chemistry of Nanoporous Gold via Electrochemical Characterization and Atom Probe Tomography Surface chemistry information is crucial in understanding catalytic and sensing mechanisms. However, resolving the outermost monolayer composition of metallic nanoporous materials is challenging due to the high tortuosity of their morphology. In this study, we first elaborate on the capabilities and limitations of atom probe tomography (APT) in resolving interfaces. Subsequently, an electrochemical approach is designed to characterize the surface composition of nanoporous gold (NPG), developed from dealloying an inexpensive precursor (95 at. % Ag, 5 at. % Au), by the means of aqueous electrochemical measurements of the selective electrosorption of sulfide ions, which react strongly with Ag, but to a significantly lesser extent with Au. Accordingly, cyclic voltammetry was performed at various scan rates on NPG in alkaline aqueous solutions (0.2 M NaOH; pH 13) in the presence and absence of 1 mM Na<sub>2</sub>S. Calibrations via similar voltammetric measurements on pure polycrystalline Ag and Au surfaces allowed for a quantitative estimation for the Ag surface coverage of NPG. The sensitivity threshold for the detection of the adsorbate-Ag interaction was assessed to be approximately 2% Ag surface coverage. As curves measured on NPG only showed featureless capacitive currents, no faradaic charge density associated with sulfide electrosorption could be detected. This study opens a new avenue to gain further insight into the monolayer surface coverage of metallic nanoporous materials and assists in enhancement of the interpretation of APT reconstructions. Nanoporous ; Monolayer ; Atom probe ; Aqueous solution ; Electrochemistry ; Cyclic voltammetry ; Materials science ; Sulfide ; Crystallite ; Metal ; Chemical engineering ; Analytical Chemistry (journal) ; Nanotechnology ; Inorganic chemistry ; Electrode ; Chemistry ; Physical chemistry ; Organic chemistry ; Metallurgy Nanoporous metals and alloys ; Advanced Materials Characterization Techniques ; Electrocatalysts for Energy Conversion
Authors: de Souza Figueiredo Katia Cecilia | de Jesus Barcelos Gustavo Feliciano | André S. Ferlauto
Source: International Journal of Membrane Science and Technology (article, 2021-11-16)
Field: Materials Science — Materials Chemistry

Graphene Membranes: From Reverse Osmosis to Gas Separation Graphene membrane is a promising technology to help both carbon dioxide separation from flue gas and water desalination. This work reported the importance of membrane separation processes, the evolution of polymeric membranes before the discovery of graphene and how this material fits into this scenario. In addition, reverse osmosis and gas separations have been discussed as promising methods to reduce the occurrence of freshwater scarcity events and slow global warming. For all these separation techniques, the current state of graphene membranes technology and what advances might be brought by such one atom thick skin layer were presented, as well as the results of theoretical and experimental research. Finally, the challenges that still need to be overcome by this innovative technology as well as the perspectives were shown. Reverse osmosis ; Graphene ; Membrane ; Desalination ; Gas separation ; Materials science ; Membrane technology ; Flue gas ; Nanotechnology ; Process engineering ; Environmental science ; Chemical engineering ; Waste management ; Engineering ; Chemistry Graphene research and applications ; Membrane Separation Technologies ; Membrane Separation and Gas Transport
Authors: Ramón Castañeda-Priego
Source: Revista Mexicana de Física (article, 2021-08-18)
Field: Materials Science — Materials Chemistry

Colloidal Soft Matter Physics Colloidal soft matter is a class of materials that exhibit rich equilibrium and non-equilibrium 0thermodynamic properties, it self-assembles (spontaneously or driven externally) to form a large diversity of structures, and its constituents display an interesting and complex transport behavior. In this contribution, we review the essential aspects and the modern challenges of Colloidal SoftMatter Physics. Our main goal is to provide a balanced discussion of the various facets of this highly multidisciplinary field, including experiments, theoretical approximations and models for molecular simulations, so that readers with various backgrounds could get both the basics and a broader, more detailed physical picture of the field. To this end, we first put emphasis on the colloidal physics, which allows us to understand the main driving (molecular and thermodynamic) forces between colloids that give rise to a wide range of physical phenomena. We also draw attention to some particular problems and areas of opportunity in Colloidal Soft Matter Physics that represent promising perspectives for future investigations. Soft matter ; Nanotechnology ; Colloid ; Field (mathematics) ; Physics ; Active matter ; Colloidal particle ; Variety (cybernetics) ; Theoretical physics ; Statistical physics ; Computer science ; Materials science ; Chemistry ; Artificial intelligence ; Biology ; Mathematics Pickering emulsions and particle stabilization ; Advanced Thermodynamics and Statistical Mechanics ; Material Dynamics and Properties
Authors: Giulia Mancardi | Matteo Alberghini | Neus Aguilera-Porta | Mónica Calatayud | Pietro Asinari | Eliodoro Chiavazzo
Source: Preprints.org (preprint, 2021-12-16)
Field: Materials Science — Materials Chemistry

A Multi-Scale Modelling of Aggregation of TiO2 Nanoparticle Suspensions in Water Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO2 nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetic described by the Smoluchowski theory. Molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, without having to conduct large scale experiments on living organisms. Nanoparticle ; Brownian dynamics ; Molecular dynamics ; Quantitative structure–activity relationship ; Brownian motion ; Density functional theory ; Statistical physics ; Titanium dioxide ; Nanomaterials ; Biological system ; Scale (ratio) ; Nanotechnology ; Materials science ; Chemical physics ; Chemistry ; Computational chemistry ; Computer science ; Physics ; Machine learning Nanoparticles: synthesis and applications ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Dirk Ziegenbalg | Andrea Pannwitz | Sven Rau | Benjamin Dietzek‐Ivanšić | Carsten Streb
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2021-10-18)
Field: Materials Science — Materials Chemistry

Challenges and Concepts for Comparative Evaluation of Light-Driven Catalysis Light-driven homogeneous and heterogeneous catalysis requires a complex interplay between light-absorption, charge-separation, charge transfer and catalytic turnover. Optical and irradiation parameters as well as reaction engineering aspects play major roles in controlling catalytic performance. This multitude of factors makes it difficult to objectively compare light-driven catalysts and provide an unbiased performance assessment. This Scientific Perspective describes the current state of the art in collecting and reporting experimental data in homogeneous and heterogeneous light-driven catalysis. A critical analysis of the benefits and limitations of the commonly used experimental indicators is provided. Data collection and reporting according to FAIR principles is discussed in the context of future automated Big Data analytical approaches. Finally, the authors propose a minimum dataset as a basis for unified collecting and reporting of experimental data in homogeneous and heterogeneous light-driven catalysis. Nanotechnology ; Computer science ; Biochemical engineering ; Materials science ; Engineering Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Polyoxometalates: Synthesis and Applications
Authors: K. Ganesh Kumar | P. Balaji Bhargav | K Aravinth | C. Balaji
Source: Research Square (preprint, 2021-09-24)
Field: Materials Science — Materials Chemistry

Enhanced Photoluminescence Properties of BaAl2O4: Ce3+/Li+ Yellow Phosphors Abstract Ce 3+ / Li + activated barium aluminate phosphor (BAO) was synthesized by conventional solid-state reaction method. The crystal structure of the synthesized phosphor was analyzed by X-ray diffraction (XRD) and Raman spectroscopy analysis. FT-IR spectrum results revealed the characteristic vibration bands present in the synthesized phosphor. Surface composition analysis of the prepared samples was examined using X-ray photoelectron spectroscopy (XPS). PL emission band observed at 589 nm was assigned to 5D excited level corresponding to 2 F 5 / 2 transition in yellow region under the excitation wavelength of 320 nm. Yellow light emission was confirmed by the Commission Internationale de L’Eclairage (CIE) chromatic coordinate graph. The color purity of BAO: 0.5Ce 3+ , BAO: 0.5Ce 3+ , 0.1Li + was found to be 78.4 %, 81.3 % whereas the measured lifetime was 4.333, 4.738 ns respectively. Phosphor ; X-ray photoelectron spectroscopy ; Raman spectroscopy ; Photoluminescence ; Analytical Chemistry (journal) ; Materials science ; Barium ; Excited state ; Spectroscopy ; Luminescence ; Crystal structure ; Chemistry ; Crystallography ; Optics ; Nuclear magnetic resonance ; Optoelectronics ; Physics ; Atomic physics Luminescence Properties of Advanced Materials ; Ammonia Synthesis and Nitrogen Reduction ; Radiation Detection and Scintillator Technologies
Authors: Ali Faghihi Zarandi | Mohammad Reza Rezaei Kahkha | Mohammad Bagher Aghebatbekheir | Nasser Hasheminejad
Source: Analytical Methods in Environmental Chemistry Journal (article, 2021-12-01)
Field: Chemistry — Inorganic Chemistry

Removal of benzene vapor from the air based on novel tantalum metal-organic framework (Ta-MOF) adsorbent by gas flow solid-phase interaction before determination by gas chromatography ‌Benzene has a carcinogenic effect on the human body and adsorption from the air is the best way to control it. By this research, benzene vapor was removed from the air based on a tantalum metal-organic framework (Ta-MOF) by gas flow solid-phase interaction (GF-SPI). Benzene adsorption with Ta-MOF was studied in the static and dynamic systems at room temperature. The benzene concentration was analyzed by gas chromatography equipped with an FID detector (GC-FID). The factors affecting benzene removal efficiency like initial concentration of benzene, amount of adsorbent, exposure time, flow rate, and temperature were studied and optimized. The results showed us, the adsorption capacities range of Ta-MOF for benzene in the static and dynamic system were obtained between 90-160 mg g-1 and 65-135 mg g-1, respectively. Also, the high removal efficiency was achieved by more than 95% at 45°C, 67.5 mg L-1 benzene concentration, 0.5 g of Ta-MOF, and the flow rate of 250 mL min-1 for a dynamic system. By dynamic system, the benzene is generated in the chamber, stored in a bag, and then moved on the surface of Ta-MOF. The GF-SPI method was validated by GC-MS and spiking real samples. Benzene ; Adsorption ; Tantalum ; Volumetric flow rate ; Chemistry ; Gas chromatography ; Metal-organic framework ; Analytical Chemistry (journal) ; Metal ; Materials science ; Chromatography ; Organic chemistry ; Thermodynamics Metal-Organic Frameworks: Synthesis and Applications ; Gas Sensing Nanomaterials and Sensors ; Catalytic Processes in Materials Science
Authors: Ryther Anderson | Diego A. Gómez‐Gualdrón
Source: ChemRxiv (preprint, 2021-02-26)
Field: Chemistry — Inorganic Chemistry

Deep Learning Combined with IAST to Screen Thermodynamically Feasible MOFs for Adsorption-Based Separation of Multiple Binary Mixtures This study demonstrates the coupling of a multipurpose multilayer perceptron (MLP) model that predicts single-component adsorption for a various molecules with ideal adsorption solution theory (IAST). The resulting computational framework predicts MOF separations properties for various binary mixtures at various compositions and pressures. The accuracy of the MLP+IAST framework was sufficiently high so that, for a given separation, MOFs in the 90th percentile from MLP+IAST-based screening contain ~87% of MOFs in the 95th percentile one would obtain from molecular simulation-based screening. Clustering algorithms were shown effective to identify so-called "privileged" MOFs that were high-performing for multiple separations. Free energy calculations were performed to determine privileged MOFs that were likely to be accesses synthetically, at least from a thermodynamic perspective. Binary number ; Adsorption ; Computer science ; Perceptron ; Cluster analysis ; Component (thermodynamics) ; Multilayer perceptron ; Separation (statistics) ; Biological system ; Materials science ; Artificial neural network ; Artificial intelligence ; Chemistry ; Thermodynamics ; Physics ; Machine learning ; Physical chemistry ; Mathematics Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Catalytic Processes in Materials Science
Authors: Derya Güngördü Solğun | Ümit Yıldıko | Mehmet Salih Ağırtaş
Source: Polycyclic aromatic compounds (article, 2021-09-27)
Field: Materials Science — Materials Chemistry

Synthesis, DFT Calculations, Photophysical, Photochemical Properties of Peripherally Metallophthalocyanines Bearing (2-(Benzo[d] [1,3] Dioxol-5-Ylmethoxy) Phenoxy) Substituents 4-(2-(benzo[d] [1,3] dioxol-5-ylmethoxy) phenoxy) phthalonitrile was first prepared as a starting material. Then, this new phthalonitrile derivative was reacted with Zn and Co salts to obtain new phthalocyanine complexes. Phthalocyanine complexes were evaluated by fluorescence emission, extinction, and absorption measurements. Aggregation studies show compliance with the lambert-beer law in the concentration range studied for peripheral phthalocyanine compounds. The density functional theory calculations of the metallophthalocyanines compounds were performed using the B3LYP method- LanL2DZ basis set to derive structural optimization, HOMO-LUMO energy parameters, and nonlinear Optical properties. The calculated values of metallophthalocyanines with different center atoms were obtained close to each other. Molecular electronic surface maps of the studied compounds are mapped and discussed. The HOMO-LUMO energy gaps of our compounds studied are around 2.1 eV. The docking studies were performed with the phthalonitrile. Phthalonitrile ; Chemistry ; Phthalocyanine ; HOMO/LUMO ; Photochemistry ; Fluorescence ; Time-dependent density functional theory ; Density functional theory ; Molar absorptivity ; Computational chemistry ; Molecule ; Organic chemistry ; Optics Porphyrin and Phthalocyanine Chemistry ; Photochemistry and Electron Transfer Studies ; Organic Chemistry Cycloaddition Reactions
Authors: Muratahan Aykol | Joseph H. Montoya | Jens S. Hummelshøj
Source: ChemRxiv (preprint, 2021-01-13)
Field: Materials Science — Materials Chemistry

Rational Solid-State Synthesis Routes for Inorganic Materials Rational solid-state synthesis of inorganic compounds is formulated as catalytic nucleation on crystalline reactants, where contributions of reaction and interfacial energies to the nucleation barriers are approximated from high-throughput thermochemical data, and structural and interfacial features of crystals, respectively. Favorable synthesis reactions are then identified by a Pareto analysis of relative nucleation barriers and phase-selectivities of reactions leading to the target. We demonstrate the application of this approach in reaction planning for solid-state synthesis of a range of compounds, including the widely-studied oxides LiCoO2, BaTiO3 and YBa2Cu3O7, as well as other metal oxide, oxyfluoride, phosphate and nitride targets. Pathways for enabling retrosynthesis of inorganics are also discussed. Nucleation ; Solid-state ; Nitride ; Materials science ; Catalysis ; Oxide ; Phase (matter) ; Chemical engineering ; Metal ; Nanotechnology ; Inorganic chemistry ; Chemistry ; Physical chemistry ; Metallurgy ; Organic chemistry Catalytic Processes in Materials Science ; X-ray Diffraction in Crystallography ; Zeolite Catalysis and Synthesis
Authors: Emmanuel Clouet | Baptiste Bienvenu | Lucile Dézerald | David Rodney
Source: Comptes Rendus Physique (preprint, 2021-06-09)
Field: Materials Science — Materials Chemistry

Screw dislocations in BCC transition metals: from ab initio modeling to yield criterion We show here how density functional theory calculations can be used to predict the temperature- and orientation-dependence of the yield stress of body-centered cubic (BCC) metals in the thermally-activated regime where plasticity is governed by the glide of screw dislocations with a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>1</mml:mn> <mml:mo>/</mml:mo> <mml:mn>2</mml:mn> <mml:mo>〈</mml:mo> <mml:mn>111</mml:mn> <mml:mo>〉</mml:mo> </mml:mrow> </mml:math> Burgers vector. Our numerical model incorporates non-Schmid effects, both the twinning/antitwinning asymmetry and non-glide effects, characterized through ab initio calculations on straight dislocations. The model uses the stress-dependence of the kink-pair nucleation enthalpy predicted by a line tension model also fully parameterized on ab initio calculations. The methodology is illustrated here on BCC tungsten but is applicable to all BCC metals. Comparison with experimental data allows to highlight both the successes and remaining limitations of our modeling approach. Materials science ; Ab initio ; Crystal twinning ; Nucleation ; Dislocation ; Condensed matter physics ; Burgers vector ; Yield (engineering) ; Thermodynamics ; Ab initio quantum chemistry methods ; Tungsten ; Density functional theory ; Asymmetry ; Crystallography ; Computational chemistry ; Chemistry ; Physics ; Metallurgy ; Quantum mechanics Microstructure and mechanical properties ; Metal and Thin Film Mechanics ; Boron and Carbon Nanomaterials Research