jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Martí Gimferrer | Sergi Danés | Diego M. Andrada | Pedro Salvador
Source: Inorganic Chemistry (article, 2021-11-12)
Field: Chemistry — Organic Chemistry

Unveiling the Electronic Structure of the Bi(+1)/Bi(+3) Redox Couple on NCN and NNN Pincer Complexes Low-valent group 15 compounds stabilized by pincer ligands have gained particular interest, given their direct access to fine-tune their reactivity by the coordination pattern. Recently, bismuth has been employed in a variety of catalytic transformations by taking advantage of the (+1/+3) redox couple. In this work, we present a detailed quantum-chemical study on the electronic structure of bismuth pincer complexes from two different families, namely, bis(ketimine)phenyl (NCN) and triamide bismuthinidene (NNN). The use of the so-called effective oxidation state analysis allows the unambiguous assignation of the bismuth oxidation state. In contrast to previous studies, our calculations suggest a Bi(+1) assignation for NCN pincer ligands, while Bi(+3) character is found for NNN pincer complexes. Notably, regardless of its oxidation state, the central bismuth atom disposes of up to two lone pairs for coordinating Lewis acids, as indicated by very high first and second proton affinity values. Besides, the Bi-NNN systems can also accommodate two Lewis base ligands, indicating also ambiphilic behavior. The effective fragment orbital analysis of Bi and the ligand allows monitoring of the intricate electron flow of these processes, revealing the noninnocent nature of the NNN ligand, in contrast with the NCN one. By the dissection of the electron density into effective fragment orbitals, we are able to quantify and rationalize the Lewis base/acid character. Chemistry ; Bismuth ; Lewis acids and bases ; Lone pair ; Oxidation state ; Pincer movement ; Pincer ligand ; Reactivity (psychology) ; Ligand (biochemistry) ; Redox ; Atomic orbital ; Crystallography ; Stereochemistry ; Catalysis ; Molecule ; Inorganic chemistry ; Electron ; Organic chemistry Organoboron and organosilicon chemistry ; Synthesis and characterization of novel inorganic/organometallic compounds ; Coordination Chemistry and Organometallics
Authors: Sobhi Daniel | Praveena Manimunda | E. M. Mohammed
Source: Materials Science and Engineering B (article, 2021-04-02)
Field: Materials Science — Materials Chemistry

Exploration of highly photoluminescent first-row transition metals (manganese, iron, cobalt, nickel, copper and zinc) co-doped nano carbon dots as energy storage materials Materials science ; Photoluminescence ; Carbon fibers ; Nanodot ; Doping ; Transition metal ; Analytical Chemistry (journal) ; Nanotechnology ; Inorganic chemistry ; Optoelectronics ; Chemistry ; Composite number ; Composite material Carbon and Quantum Dots Applications ; Supercapacitor Materials and Fabrication ; Quantum Dots Synthesis And Properties
Authors: Sergio García‐Dalí | J.I. Paredes | S. Villar–Rodil | A. Martínez-Jódar | A. Martı́nez-Alonso | J.M.D. Tascón
Source: ACS Applied Materials & Interfaces (article, 2021-07-12)
Field: Materials Science — Materials Chemistry

Molecular Functionalization of 2H-Phase MoS<sub>2</sub> Nanosheets via an Electrolytic Route for Enhanced Catalytic Performance The molecular functionalization of two-dimensional MoS<sub>2</sub> is of practical relevance with a view to, for example, facilitating its liquid-phase processing or enhancing its performance in target applications. While derivatization of metallic 1T-phase MoS<sub>2</sub> nanosheets has been relatively well studied, progress involving their thermodynamically stable, 2H-phase counterpart has been more limited due to the lower chemical reactivity of the latter. Here, we report a simple electrolytic strategy to functionalize 2H-phase MoS<sub>2</sub> nanosheets with molecular groups derived from organoiodides. Upon cathodic treatment of a pre-expanded MoS<sub>2</sub> crystal in an electrolyte containing the organoiodide, water-dispersible nanosheets derivatized with acetic acid or aniline moieties (∼0.10 molecular groups inserted per surface sulfur atom) were obtained. Analysis of the functionalization process indicated it to be enabled by the external supply of electrons from the cathodic potential, although they could also be sourced from a proper reducing agent, as well as by the presence of intrinsic defects in the 2H-phase MoS<sub>2</sub> lattice (e.g., sulfur vacancies), where the molecular groups can bind. The acetic acid-functionalized nanosheets were tested as a non-noble metal-based catalyst for nitroarene and organic dye reduction, which is of practical utility in environmental remediation and chemical synthesis, and exhibited a markedly enhanced activity, surpassing that of other (1T- or 2H-phase) MoS<sub>2</sub> materials and most non-noble metal catalysts previously reported for this application. The reduction kinetics (reaction order) was seen to correlate with the net electric charge of the nitroarene/dye molecules, which was ascribed to the distinct abilities of the latter to diffuse to the catalyst surface. The functionalized MoS<sub>2</sub> catalyst also worked efficiently at realistic (i.e., high) reactant concentrations, as well as with binary and ternary mixtures of the reactants, and could be immobilized on a polymeric scaffold to expedite its manipulation and reuse. Materials science ; Surface modification ; Catalysis ; Molecule ; Aniline ; Electrolyte ; Chemical engineering ; Phase (matter) ; Inorganic chemistry ; Nanotechnology ; Organic chemistry ; Electrode ; Physical chemistry ; Chemistry MXene and MAX Phase Materials ; 2D Materials and Applications ; Advanced Photocatalysis Techniques
Authors: Ana C. Marques | Mário Vale
Source: Materials (review, 2021-07-29)
Field: Materials Science — Materials Chemistry

Macroporosity Control by Phase Separation in Sol-Gel Derived Monoliths and Microspheres Macroporous and hierarchically macro/mesoporous materials (mostly monoliths and microspheres) have attracted much attention for a variety of applications, such as supporting or enabling materials in chromatography, energy storage and conversion, catalysis, biomedical devices, drug delivery systems, and environmental remediation. A well-succeeded method to obtain these tailored porous materials relies on the sol-gel technique, combined with phase separation by spinodal decomposition, and involves as well emulsification as a soft template, in the case of the synthesis of porous microspheres. Significant advancements have been witnessed, in terms of synthesis methodologies optimized either for the use of alkoxides or metal-salts and material design, including the grafting or immobilization of a specific species (or nanoparticles) to enable the most recent trends in technological applications, such as photocatalysis. In this context, the evolution, in terms of material composition and synthesis strategies, is discussed in a concerted fashion in this review, with the goal of inspiring new improvements and breakthroughs in the framework of porous materials. Materials science ; Mesoporous material ; Context (archaeology) ; Nanotechnology ; Porosity ; Photocatalysis ; Porous medium ; Microsphere ; Sol-gel ; Spinodal decomposition ; Drug delivery ; Chemical engineering ; Phase (matter) ; Catalysis ; Chemistry ; Organic chemistry ; Composite material ; Engineering Mesoporous Materials and Catalysis ; Aerogels and thermal insulation ; Layered Double Hydroxides Synthesis and Applications
Authors: Jingjing Zhao | Hongyi Xu | Hugo Lebrette | Marta Carroni | Helena Taberman | Martin Högbom | Xiaodong Zou
Source: Nature Communications (article, 2021-08-19)
Field: Materials Science — Materials Chemistry

A simple pressure-assisted method for MicroED specimen preparation Micro-crystal electron diffraction (MicroED) has shown great potential for structure determination of macromolecular crystals too small for X-ray diffraction. However, specimen preparation remains a major bottleneck. Here, we report a simple method for preparing MicroED specimens, named Preassis, in which excess liquid is removed through an EM grid with the assistance of pressure. We show the ice thicknesses can be controlled by tuning the pressure in combination with EM grids with appropriate carbon hole sizes. Importantly, Preassis can handle a wide range of protein crystals grown in various buffer conditions including those with high viscosity, as well as samples with low crystal concentrations. Preassis is a simple and universal method for MicroED specimen preparation, and will significantly broaden the applications of MicroED. Materials science ; Diffraction ; Nanotechnology ; Optics ; Physics Enzyme Structure and Function ; Mass Spectrometry Techniques and Applications ; Advanced Electron Microscopy Techniques and Applications
Authors: Muhammad Saqaf Jagirani | Mustafa Soylak
Source: TURKISH JOURNAL OF CHEMISTRY (review, 2021-11-30)
Field: Chemistry — Analytical Chemistry

Supramolecular solvents: a review of a modern innovation in liquid-phase microextraction technique Supramolecular solvents (SUPRASs) have rapidly gained more attention as a potential substitute to organic solvents in the sample preparation and preconcentration process. The essential properties of SUPRAS solvents (e.g., multiple binding sites, different polarity microenvironments, the opportunity to tailor their properties, etc.) these qualities offer numerous opportunities to advance innovative sample preparation and pretreatment platforms compared to the traditional solvents. Among these qualities, certain importance is placed on theoretical and practical knowledge. That has assisted in making significant developments in SUPRAS that advance our understanding of the processes behind SUPRA'S formation. The SUPRA-solute interactions that drive extractions are explored in this context to develop knowledge-based extraction techniques. This review mainly focused on the significant application of supramolecular-based solvents (SUPRASs) in microextraction techniques. SUPRASs-based liquid-phase microextraction (LPME) is an excellent tool for extracting, simple preparation, and preconcentration from complex environmental samples. SUPRASs-LPME has a wide range of applications for analyzing food, environmental samples, pharmaceuticals, and biological samples. Supramolecular chemistry ; Chemistry ; Context (archaeology) ; Sample preparation ; Liquid phase ; Extraction (chemistry) ; Nanotechnology ; Solid-phase microextraction ; Polarity (international relations) ; Chromatography ; Organic chemistry ; Materials science ; Gas chromatography–mass spectrometry ; Molecule ; Mass spectrometry Analytical chemistry methods development ; Molecular Sensors and Ion Detection ; Mass Spectrometry Techniques and Applications
Authors: Marina Rosebrock | Dániel Zámbó | Pascal Rusch | Denis Pluta | Frank Steinbach | Patrick Bessel | Anja Schlosser | Armin Feldhoff | Karen D. J. Hindricks | Peter Behrens | Dirk Dorfs | Nadja C. Bigall
Source: Advanced Functional Materials (article, 2021-06-01)
Field: Materials Science — Materials Chemistry

Spatial Extent of Fluorescence Quenching in Mixed Semiconductor–Metal Nanoparticle Gel Networks Abstract In this work, mixing and co‐gelation of Au nanoparticles (NPs) and highly luminescent CdSe/CdS core/shell nanorods (NRs) are used as tools to obtain noble metal particle‐decorated macroscopic semiconductor gel networks. The hybrid nature of the macrostructures facilitates the control over the optical properties: while the holes are trapped in the CdSe cores, the connected CdSe/CdS NRs support the mobility of excited electrons throughout the porous, hyperbranched gel networks. Due to the presence of Au NPs in the mixed gels, electron trapping in the gold NPs leads to a suppressed radiative recombination, namely, quenches the fluorescence in certain fragments of the multicomponent gel. The extent of fluorescence quenching can be influenced by the quantity of the noble metal domains. The optical properties are monitored as a function of the NR:NP ratio of a model system CdSe/CdS:Au. By this correlation, it demonstrates that the spatial extent of quenching initiated by a single Au NP exceeds the dimensions of one NR, which the Au is connected to (with a length of 45.8 nm ± 4.1 nm) and can reach the number of nine NRs per Au NP, which roughly corresponds to 400 nm of total electron travel distance within the network structure. Materials science ; Quenching (fluorescence) ; Noble metal ; Nanoparticle ; Nanorod ; Fluorescence ; Luminescence ; Particle (ecology) ; Semiconductor ; Chemical physics ; Electron ; Excited state ; Nanotechnology ; Metal ; Optoelectronics ; Atomic physics ; Optics ; Physics Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Aerogels and thermal insulation
Authors: Jurjen A. Regenspurg | Ana Martins Costa | Iske Achterhuis | Wiebe M. de Vos
Source: ACS Applied Polymer Materials (review, 2021-09-23)
Field: Materials Science — Surfaces, Coatings and Films

Influence of Molecular Weight on the Performance of Polyelectrolyte Multilayer Nanofiltration Membranes Polyelectrolyte multilayers (PEMs) are highly promising selective layers for membrane applications, especially because of their versatility. By careful choice of the types of polyelectrolyte and the coating conditions, the PEM material properties can be controlled to achieve desired separations. Less understood, however, is how the molecular weight (Mw) of the chosen polyelectrolytes (PEs) will impact layer build-up and thus separation properties. In this work, we investigate the influence of Mw on the performance of two types of PEM-based membranes. PEM membranes have been fabricated from low (15-20 kDa) and high (150-250 kDa) Mw poly(allylamine hydrochloride) (PAH), poly(sodium-4-styrenesulfonate)(PSS), and poly(acrylic acid) (PAA) to obtain PAH/PSS- and PAH/PAA-based nanofiltration membranes. For the linear growing PSS/PAH system, with low PE mobility, the Mw is found to influence the pore closure of the support membrane during coating but not its subsequent performance. In contrast, for the exponentially growing PAH/PAA system with a high PE mobility, much stronger effects of Mw are observed. For low-Mw PAH/PAA PEM membranes, separation properties are found that would be expected of a negatively charged separation layer, while for high-Mw PAH/PAA PEMs a positive separation layer is found. Moreover, molecular weight cutoff (MWCO) measurements show that the low-Mw PAH/PAA multilayers are much denser than their high-Mw counterparts. Here the higher mobility of the small PE chains is expected to lead to more optimal binding between the oppositely charged PEs, explaining the denser structure. Lastly, we find that PEM pH stability is lowest for low-Mw PAH/PAA multilayers which can again be attributed to their higher mobility. Clearly, the Mw can significantly influence the separation performance of PEM-based membranes, especially for more mobile PEM systems such as PAA/PAH. Polyelectrolyte ; Nanofiltration ; Membrane ; Chemical engineering ; Allylamine ; Coating ; Acrylic acid ; Layer by layer ; Layer (electronics) ; Polymer chemistry ; Materials science ; Chemistry ; Copolymer ; Polymer ; Organic chemistry ; Nanotechnology Polymer Surface Interaction Studies ; Membrane Separation Technologies ; Electrospun Nanofibers in Biomedical Applications
Authors: D. O. Oriekhov | V. P. Gusynin | В. М. Локтев
Source: Physical review. B./Physical review. B (article, 2021-05-03)
Field: Materials Science — Materials Chemistry

Orbital susceptibility of T-graphene: Interplay of high-order van Hove singularities and Dirac cones Square-octagon lattice underlies the description of a family of two-dimensional materials such as tetragraphene. In the present paper we show that the tight-binding model of square-octagon lattice contains both conventional and high-order van Hove points. In particular, the spectrum of the model contains flat lines along some directions composed of high-order saddle points. Their role is analyzed by calculating the orbital susceptibility of electrons. We find that the presence of van Hove singularities (VHS) of different kinds in the density of states leads to strong responses: paramagnetic for ordinary singularities and more complicated for high-order singularities. It is shown that at doping level of high-order VHS the orbital susceptibility as a function of hoppings ratio $\ensuremath{\alpha}$ reveals the dia- to paramagnetic phase transition at $\ensuremath{\alpha}\ensuremath{\approx}0.94$. This is due to the competition of paramagnetic contribution of high-order VHS and diamagnetic contribution of Dirac cones. The results for the tight-binding model are compared with the low-energy effective pseudospin-1 model near the three band touching point. Physics ; Van Hove singularity ; Condensed matter physics ; Paramagnetism ; Square lattice ; Density of states ; Gravitational singularity ; Pairing ; Tight binding ; Diamagnetism ; Electron ; Quantum mechanics ; Electronic structure ; Magnetic field ; Fermi level ; Superconductivity ; Ising model Graphene research and applications ; Topological Materials and Phenomena ; Quantum and electron transport phenomena
Authors: Junwoong Yoon | Zhonglin Cao | Rajesh K. Raju | Yuyang Wang | Robert Burnley | Andrew J. Gellman | Amir Barati Farimani | Zachary W. Ulissi
Source: Machine Learning Science and Technology (article, 2021-07-29)
Field: Materials Science — Materials Chemistry

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy Abstract The majority of computational catalyst design focuses on the screening of material components and alloy composition to optimize selectivity and activity for a given reaction. However, predicting the metastability of the alloy catalyst surface at realistic operating conditions requires an extensive sampling of possible surface reconstructions and their associated kinetic pathways. We present CatGym, a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions. We showcase our agent by predicting the surface reconstruction pathways of a ternary Ni 3 Pd 3 Au 2 (111) alloy catalyst. Our results show that the DRL agent can not only explore more diverse surface compositions than the conventional minima hopping method, but also generate the kinetic surface reconstruction pathways. We further demonstrate that the kinetic pathway to a global minimum energy surface composition and its associated transition state predicted by our agent is in good agreement with the minimum energy path predicted by nudged elastic band calculations. Metastability ; Ternary operation ; Kinetic energy ; Maxima and minima ; Materials science ; Surface reconstruction ; Alloy ; Potential energy surface ; Surface (topology) ; Chemical physics ; Catalysis ; Chemistry ; Computer science ; Molecule ; Physics ; Composite material ; Mathematics ; Geometry Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Catalytic Processes in Materials Science
Authors: Zhen Zhou
Source: Journal of Materials Chemistry A (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

<i>Journal of Materials Chemistry A</i> and <i>Materials Advances</i> Editor’s choice web collection: “Machine learning for materials innovation” Zhen Zhou introduces a <italic>Journal of Materials Chemistry</italic>/<italic>Materials Advances</italic> Editor’s choice web collection on machine learning for materials innovation (https://rsc.li/MachineLearning). Engineering ; Nanotechnology ; Library science ; Engineering physics ; Computer science ; Materials science Machine Learning in Materials Science
Authors: B. O. Mukhamedov | K. V. Karavaev | Igor A. Abrikosov
Source: Physical Review Materials (article, 2021-10-18)
Field: Materials Science — Metals and Alloys

Machine learning prediction of thermodynamic and mechanical properties of multicomponent Fe-Cr-based alloys We apply machine learning algorithms to optimize thermodynamic and elastic properties of multicomponent Fe-Cr alloys with additions of Ni, Mo, Al, W, V, and Nb. The target properties are mixing enthalpy, Young's elastic modulus, and the ratio between shear and bulk moduli, which is often used as a phenomenological criterion for a material's ductility. We thoroughly analyze the descriptors that provide the robust performance of the machine learning models. Next, the iterative active learning method is used for the optimization of the chemical composition to simultaneously improve both thermodynamic stability and the elastic properties of Fe-Cr-based alloys. As a result, we predict compositions of thermodynamically stable alloys with improved mechanical properties, demonstrating the high potential of data-driven computational design in the field of materials for nuclear energy applications. Materials science ; Ductility (Earth science) ; Elastic modulus ; Thermodynamics ; Enthalpy ; Material properties ; Shear modulus ; Chemical stability ; Phenomenological model ; Mixing (physics) ; Metallurgy ; Composite material ; Condensed matter physics Hydrogen embrittlement and corrosion behaviors in metals ; Machine Learning in Materials Science ; Nuclear Materials and Properties
Authors: Jie Luo | Xun Li | Xinyuan Zhang | Jiajie Guo | Wei Liu | Yun Lai | Yaohui Zhan | Min Huang
Source: Optics Express (article, 2021-03-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Deep-learning-enabled inverse engineering of multi-wavelength invisibility-to-superscattering switching with phase-change materials Inverse design of nanoparticles for desired scattering spectra and dynamic switching between the two opposite scattering anomalies, i.e. superscattering and invisibility, is important in realizing cloaking, sensing and functional devices. However, traditionally the design process is quite complicated, which involves complex structures with many choices of synthetic constituents and dispersions. Here, we demonstrate that a well-trained deep-learning neural network can handle these issues efficiently, which can not only forwardly predict scattering spectra of multilayer nanoparticles with high precision, but also inversely design the required structural and material parameters efficiently. Moreover, we show that the neural network is capable of finding out multi-wavelength invisibility-to-superscattering switching points at the desired wavelengths in multilayer nanoparticles composed of metals and phase-change materials. Our work provides a useful solution of deep learning for inverse design of nanoparticles with dynamic scattering spectra by using phase-change materials. Cloaking ; Invisibility ; Materials science ; Scattering ; Wavelength ; Phase (matter) ; Optics ; Inverse problem ; Inverse scattering problem ; Artificial neural network ; Computer science ; Inverse ; Optoelectronics ; Metamaterial ; Physics ; Artificial intelligence ; Mathematics Metamaterials and Metasurfaces Applications ; Phase-change materials and chalcogenides ; Advanced Memory and Neural Computing