jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Christoph Gertig | Lorenz Fleitmann | Carl Hemprich | Janik Hense | André Bardow | Kai Leonhard
Source: Computers & Chemical Engineering (article, 2021-07-08)
Field: Materials Science — Materials Chemistry

CAT-COSMO-CAMPD: Integrated in silico design of catalysts and processes based on quantum chemistry Catalysts are of paramount importance as most chemical processes would be uneconomical without suitable catalysts. Consequently, the identification of appropriate catalysts is a key step in chemical process design. However, the number of potential catalysts is usually vast. To suggest promising candidates for experimental testing, in silico catalyst design methods are highly desirable. Still, such computational methods are in their infancy. Moreover, simple performance indicators are commonly employed as design objective instead of evaluating the actual process performance enabled by considered catalysts. Here, we present the CAT-COSMO-CAMPD method for integrated in silico design of homogeneous molecular catalysts and processes. CAT-COSMO-CAMPD integrates design of molecular catalysts with process optimization, enabling a process-based evaluation of every designed candidate catalyst. Reaction kinetics of catalytic reactions are predicted by advanced quantum chemical methods. We demonstrate for a catalytic carbamate-cleavage process that CAT-COSMO-CAMPD successfully identifies catalyst molecules maximizing the predicted process performance. Catalysis ; Quantum chemical ; In silico ; Rational design ; Chemistry ; Process (computing) ; Process design ; Biochemical engineering ; COSMO-RS ; Process engineering ; Combinatorial chemistry ; Computer science ; Process integration ; Nanotechnology ; Materials science ; Molecule ; Organic chemistry ; Engineering Machine Learning in Materials Science ; Zeolite Catalysis and Synthesis ; Catalytic Processes in Materials Science
Authors: Kirsten M. Ø. Jensen
Source: CHIMIA International Journal for Chemistry (article, 2021-05-21)
Field: Materials Science — Materials Chemistry

Characterization of Nanomaterials with Total Scattering and Pair Distribution Function Analysis: Examples from Metal Oxide Nanochemistry The development of new functional nanomaterials builds on an understanding of the intricate relation between material structure and properties. Only by knowing the atomic arrangement can the mechanisms responsible for material properties be elucidated and new materials and technologies developed. Nanomaterials challenge the crystallographic techniques often used for structure characterization, and the structure of many nanomaterials are therefore often assumed to be 'cut-outs' of the corresponding bulk material. Here, I will discuss how Pair Distribution Function (PDF) analysis of total scattering data can aid nanochemists in obtaining a structural understanding of nanoscale materials, focusing on examples from metal oxide chemistry. Nanomaterials ; Nanochemistry ; Characterization (materials science) ; Nanotechnology ; Materials science ; Oxide ; Pair distribution function ; Nanoscopic scale ; Function (biology) ; Physics ; Metallurgy X-ray Diffraction in Crystallography ; Crystal Structures and Properties ; Nuclear materials and radiation effects
Authors: Ethan F. Bull-Vulpe | Marc Riera | Andreas Goetz | Francesco Paesani
Source: ChemRxiv (preprint, 2021-07-13)
Field: Materials Science — Materials Chemistry

MB-Fit: Software Infrastructure for Data-Driven Many-Body Potential Energy Functions Many-body potential energy functions (MB-PEFs), which integrate data-driven representations of many-body short-range quantum mechanical interactions with physics-based representations of many-body polarization and long-range interactions, have recently been shown to provide high accuracy in the description of molecular interactions, from the gas to the condensed phase. Here, we present MB-Fit, a software infrastructure for the auto- mated development of MB-PEFs for generic molecules within the TTM-nrg (“Thole-type model energy”) and MB-nrg (“many-body energy”) theoretical frameworks. Besides providing all the necessary computational tools for generating TTM-nrg and MB-nrg PEFs, MB-Fit provides a seamless interface with the MBX software, a many-body energy/force calculator for computer simulations. Given the demonstrated accuracy of the MB-PEFs, we believe that MB-Fit will enable routine, predictive computer simulations of generic (small) molecules in the gas, liquid, and solid phases, including, but not limited to, the modeling of isomeric equilibria in molecular clusters, solvation processes, molecular crystals, and phase diagrams. Software ; Range (aeronautics) ; Potential energy ; Calculator ; Computer science ; Solvation ; Statistical physics ; Energy (signal processing) ; Interface (matter) ; Physics ; Computational science ; Molecule ; Materials science ; Classical mechanics ; Quantum mechanics Machine Learning in Materials Science ; Phase Equilibria and Thermodynamics ; Catalysis and Oxidation Reactions
Authors: Neil L. Allan | Sergio Conejeros | Judy N. Hart | Chris E. Mohn
Source: Theoretical Chemistry Accounts (article, 2021-10-16)
Field: Materials Science — Materials Chemistry

Energy landscapes of perfect and defective solids: from structure prediction to ion conduction Abstract The energy landscape concept is increasingly valuable in understanding and unifying the structural, thermodynamic and dynamic properties of inorganic solids. We present a range of examples which include (i) structure prediction of new bulk phases including carbon nitrides, phosphorus carbides, LiMgF 3 and low-density, ultra-flexible polymorphs of B 2 O 3, (ii) prediction of graphene and related forms of ZnO, ZnS and other compounds which crystallise in the bulk with the wurtzite structure, (iii) solid solutions, (iv) understanding grossly non-stoichiometric oxides including the superionic phases of δ-Bi 2 O 3 and BIMEVOX and the consequences for the mechanisms of ion transport in these fast ion conductors. In general, examination of the energy landscapes of disordered materials highlights the importance of local structural environments, rather than sole consideration of the average structure. Wurtzite crystal structure ; Nitride ; Ion ; Chemical physics ; Materials science ; Fast ion conductor ; Carbide ; Stoichiometry ; Carbon fibers ; Energy landscape ; Range (aeronautics) ; Graphene ; Crystallography ; Chemistry ; Nanotechnology ; Thermodynamics ; Hexagonal crystal system ; Physical chemistry ; Physics ; Organic chemistry Nuclear materials and radiation effects ; Electronic and Structural Properties of Oxides ; Advanced Condensed Matter Physics
Authors: Tahereh Shah Mansouri | Hui Wang | Davide Mariotti | Paul Maguire
Source: Ulster University Research Portal (Ulster University) (article, 2021-09-13)
Field: Chemistry — Spectroscopy

Methane detection to 1 ppm using machine learning analysis of atmospheric pressure plasma optical emission spectra Abstract: Optical emission spectroscopy from a small-volume, 5 μl, atmospheric pressure RF-driven helium plasma was used in conjunction with partial least squares-discriminant analysis for the detection of trace concentrations of methane gas. A limit of detection of 1 ppm was obtained and sample concentrations up to 100 ppm CH4 were classified using a nine-category model. A range of algorithm enhancements were investigated including regularization, simple data segmentation and subset selection, feature selection via Variable Importance in Projection and wavelength variable compression in order to address the high dimensionality and collinearity of spectral emission data. These approaches showed the potential for significant reduction in the number of wavelength variables and the spectral resolution/bandwidth. Wavelength variable compression exhibited reliable predictive performance, with accuracy values &gt;97%, under more challenging multi-session train—test scenarios. Simple modelling of plasma electron energy distribution functions highlights the complex cross-sensitivities between the target methane, its dissociation products and atmospheric impurities and their impact on excitation and emission. Feature selection ; Collinearity ; Chemistry ; Emission spectrum ; Atmospheric pressure ; Wavelength ; Spectroscopy ; Spectral line ; Analytical Chemistry (journal) ; Optics ; Physics ; Computer science ; Mathematics ; Artificial intelligence ; Statistics Spectroscopy and Laser Applications ; Advanced Chemical Sensor Technologies ; Spectroscopy and Chemometric Analyses
Authors: Kohei Aso | Jens Maebe | Xuan Quy Tran | Tomokazu Yamamoto | Yoshifumi Oshima | Syo Matsumura
Source: ACS Nano (article, 2021-07-07)
Field: Materials Science — Materials Chemistry

Subpercent Local Strains Due to the Shapes of Gold Nanorods Revealed by Data-Driven Analysis Analysis of subpercent local strain is important for a deeper understanding of nanomaterials, whose properties often depend on the strain. Conventional strain analysis has been performed by measuring interatomic distances from scanning transmission electron microscopy (STEM) images. However, measuring subpercent strain remains a challenge because the peak positions in STEM images do not precisely correspond to the real atomic positions due to disturbing influences, such as random noise and image distortion. Here, we utilized an advanced data-driven analysis method, Gaussian process regression, to predict the true strain distribution by reconstructing the true atomic positions. As a result, a precision of 0.2% was achieved in strain measurement at the atomic scale. The method was applied to gold nanoparticles of different shapes to reveal the shape dependence of the strain distribution. A spherical gold nanoparticle showed a symmetric strain distribution with a contraction of ∼1% near the surface owing to surface relaxation. By contrast, a gold nanorod, which is a cylinder terminated by hemispherical caps on both sides, showed nonuniform strain distributions with lattice expansions of ∼0.5% along the longitudinal axis around the caps except for the contraction at the surface. Our results indicate that the strain distribution depends on the shape of the nanomaterials. The proposed data-driven analysis is a convenient and powerful tool to measure the strain distribution with high precision at the atomic scale. Materials science ; Nanorod ; Nanomaterials ; Strain (injury) ; Atomic units ; Nanotechnology ; Scanning transmission electron microscopy ; Transmission electron microscopy ; Physics Machine Learning in Materials Science ; Force Microscopy Techniques and Applications ; Microstructure and mechanical properties
Authors: Mariano Ortega‐Muñoz | Paula Vargas-Navarro | Simona Plesselova | María D. Girón | Guillermo R. Iglesias | Rafael Salto | Fernando Hernández-Matéo | Á.V. Delgado | Javier López-Jaramillo | Francisco Santoyo‐González
Source: Materials Chemistry Frontiers (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Amphiphilic-like carbon dots as antitumoral drug vehicles and phototherapeutical agents Amphiphilic-like carbon dots bearing ionizable carboxylate groups and hydrophobic alkyl chains entrap hydrophobic molecules and solubilize them in aqueous systems. In nanomedicine they can be used as drug delivery systems and phototherapeutic agents. Amphiphile ; Nanomedicine ; Alkyl ; Drug delivery ; Aqueous solution ; Molecule ; Carbon chain ; Chemistry ; Carboxylate ; Amphiphilic molecule ; Carbon fibers ; Drug ; Solubilization ; Liposome ; Combinatorial chemistry ; Organic chemistry ; Nanotechnology ; Materials science ; Nanoparticle ; Copolymer ; Polymer ; Pharmacology ; Biochemistry Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Graphene and Nanomaterials Applications
Authors: Elena V. Khramenkova | Michael G. Medvedev | Guanna Li | Evgeny A. Pidko
Source: The Journal of Physical Chemistry Letters (article, 2021-11-03)
Field: Materials Science — Materials Chemistry

Unraveling the Nature of Extraframework Catalytic Ensembles in Zeolites: Flexibility and Dynamics of the Copper-Oxo Trimers in Mordenite Extraframework cations define the chemical versatility of zeolite catalysts. Addressing their structural complexity and dynamic behavior represents one of the main fundamental challenges in the field. Herein, we present a computational approach for the identification and analysis of the accessible pool of intrazeolite extraframework complexes with a Cu/MOR catalyst as an industrially important model system. We employ <i>ab initio</i> molecular dynamics for capturing the ensemble of reactive isomers with the [Cu<sub>3</sub>O<sub>3</sub>]<sup>2+</sup> stoichiometry confined in the mordenite channels. The high structural diversity of the generated isomers was ensured by concentrating the kinetic energy along the low-curvature directions of the potential energy surface (PES). Geometrically distinct [Cu<sub>3</sub>O<sub>3</sub>]<sup>2+</sup> complexes were identified via a series of clustering procedures ensuring that one structure of each local minima is retained. The proposed procedure has resulted in a set of previously unknown peroxo-complexes, which are >50 kJ/mol more stable than the recently hypothesized chair-shaped structure. Our analysis demonstrates that the most stable peroxo-containing clusters can be formed under <i>operando</i> conditions from molecular oxygen and the Cu<sub>3</sub>O unit, similar to that in methane monooxygenase (MMO) enzymes. Chemistry ; Mordenite ; Molecular dynamics ; Catalysis ; Computational chemistry ; Ab initio ; Zeolite ; Crystallography ; Chemical physics ; Organic chemistry Catalytic Processes in Materials Science ; Nanocluster Synthesis and Applications ; Metal-Catalyzed Oxygenation Mechanisms
Authors: Craig M. Williams | Madeleine A. Dallaston
Source: Australian Journal of Chemistry (article, 2021-05-11)
Field: Chemistry — Organic Chemistry

The Future of Retrosynthesis and Synthetic Planning: Algorithmic, Humanistic or the Interplay? The practice of deploying and teaching retrosynthesis is on the cusp of considerable change, which in turn forces practitioners and educators to contemplate whether this impending change will advance or erode the efficiency and elegance of organic synthesis in the future. A short treatise is presented herein that covers the concept of retrosynthesis, along with exemplified methods and theories, and an attempt to comprehend the impact of artificial intelligence in an era when freely and commercially available retrosynthetic and forward synthesis planning programs are increasingly prevalent. Will the computer ever compete with human retrosynthetic design and the art of organic synthesis? Retrosynthetic analysis ; Engineering ; Humanism ; Elegance ; Management science ; Artificial intelligence ; Engineering ethics ; Computer science ; Epistemology ; Political science ; Chemistry ; Law Chemical synthesis and alkaloids ; Chemical Synthesis and Analysis ; Microbial Natural Products and Biosynthesis
Authors: João Resende | Van Son Nguyen | Claudia Fleischmann | Lorenzo Bottiglieri | Stéphane Brochen | Wilfried Vandervorst | Wilfried Favre | Carmen Jiménez | Jean‐Luc Deschanvres | Ngoc Duy Nguyen
Source: Scientific Reports (article, 2021-04-08)
Field: Materials Science — Materials Chemistry

Grain-boundary segregation of magnesium in doped cuprous oxide and impact on electrical transport properties In this study, we report the segregation of magnesium in the grain boundaries of magnesium-doped cuprous oxide (Cu<sub>2</sub>O:Mg) thin films as revealed by atom probe tomography and the consequences of the dopant presence on the temperature-dependent Hall effect properties. The incorporation of magnesium as a divalent cation was achieved by aerosol-assisted metal organic chemical vapour deposition, followed by thermal treatments under oxidizing conditions. We observe that, in comparison with intrinsic cuprous oxide, the electronic transport is improved in Cu<sub>2</sub>O:Mg with a reduction of resistivity to 13.3 ± 0.1 Ω cm, despite the reduction of hole mobility in the doped films, due to higher grain-boundary scattering. The Hall carrier concentration dependence with temperature showed the presence of an acceptor level associated with an ionization energy of 125 ± 9 meV, similar to the energy value of a large size impurity-vacancy complex. Atom probe tomography shows a magnesium incorporation of 5%, which is substantially present at the grain boundaries of the Cu<sub>2</sub>O. Grain boundary ; Materials science ; Magnesium ; Oxide ; Doping ; Dopant ; Impurity ; Analytical Chemistry (journal) ; Electrical resistivity and conductivity ; Acceptor ; Metal ; Atom (system on chip) ; Inorganic chemistry ; Hall effect ; Metallurgy ; Condensed matter physics ; Chemistry ; Microstructure Copper-based nanomaterials and applications ; Advanced Materials Characterization Techniques ; Electronic and Structural Properties of Oxides
Authors: Dong‐Jin Lee | Dae Yu Kim
Source: Scientific Reports (article, 2021-11-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

3D hotspot matrix of Au nanoparticles on Au island film with a spacer layer of dithiol molecules for highly sensitive surface-enhanced Raman spectroscopy Engineering of efficient plasmonic hotspots has been receiving great attention to enhance the sensitivity of surface-enhanced Raman scattering (SERS). In the present study, we propose a highly sensitive SERS platform based on Au nanoparticles (AuNPs) on Au island film (AuIF) with a spacer layer of 1,4-benzenedimethanethiol (BDMT). The three-dimensional (3D) hotspot matrix has been rationally designed based on the idea of employing 3D hotspots with a vertical nanogap between AuIF and AuNPs after generating large area two-dimensional hotspots of AuIF. AuNPs@BDMT@AuIF are fabricated by functionalizing BDMT on AuIF and then immobilizing AuNPs. The SERS performance is investigated with Rhodamine 6G as a probe molecule and the determined enhancement factor is 1.3 × 10<sup>5</sup>. The AuNPs@BDMT@AuIF are then employed to detect thiram, which is used as a fungicide, with a detection limit of 13 nM. Our proposed platform thus shows significant potential for use in highly sensitive SERS sensors. Dithiol ; Hotspot (geology) ; Raman spectroscopy ; Surface-enhanced Raman spectroscopy ; Nanoparticle ; Molecule ; Materials science ; Spectroscopy ; Nanotechnology ; Chemistry ; Optics ; Raman scattering ; Physics ; Biochemistry ; Organic chemistry Gold and Silver Nanoparticles Synthesis and Applications ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Katsuhiko Ariga
Source: Analytical Sciences (article, 2021-05-06)
Field: Chemistry — Spectroscopy

Nanoarchitectonics for Analytical Science at Interfaces and with Supramolecular Nanostructures Nanotechnology ; Interface (matter) ; Supramolecular chemistry ; Nanostructure ; Chemistry ; Materials science ; Molecule Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Sensors ; Machine Learning in Materials Science
Authors: Mingyang Liu | Xuejun Du | Ke Xu | Binwei Yan | Zaibi Fan | Zideng Gao | Xueqin Ren
Source: Journal of Analytical Science & Technology (article, 2021-02-24)
Field: Materials Science — Materials Chemistry

A cationic quantum dot-based ratiometric fluorescent probe to visually detect berberine hydrochloride in human blood serums Abstract Berberine hydrochloride (BH) is an isoquinoline alkaloid normally used as drug to treat diseases. Compared with the traditional detection methods, the carbon quantum dots (CQDs) have better selectivity, high sensitivity, easy operation, and is inexpensive which could be widely utilized as fluorescent nanoprobes to detect various compounds quantificationally. And ratiometric fluorescent sensors conspicuously increase sensitivity and precision detection and improve quantification. In this work, we use water-soluble and fluorescent cationic carbon dots cetylpyridinium chloride monohydrate (CPC)-CQDs to connect with pinacyanol chloride (PC) and sodium tetraphenylborate (ST) as the ratiometric fluorescent probe to detect BH. The ratiometric fluorescent probe has high sensitivity towards alkaloids and metal ions, photochemical stability (60 min), and pH stability (from 6.0 to 8.0), with the detection range from 0 to 200 μM, and limit was as low as 57.35 nM. The accuracy of the method was verified by spiked recovery experiment in different human blood serums which were drawn from healthy adult volunteers to explore the practicability. The recoveries were in the range 94.34 to 105.48% with relative standard deviations (RSD) of 0.80 to 2.92%. In addition, we could observe that the fluorescence was gradually darkened, and the color turned yellow to realize the visual detection. It is expected that this work would open up a new strategy for detecting BH in the environment and human blood serums. Fluorescence ; Detection limit ; Cationic polymerization ; Chemistry ; Berberine hydrochloride ; Cetylpyridinium chloride ; Drug detection ; Sodium tetraphenylborate ; Hydrochloride ; Berberine ; Selectivity ; Chromatography ; Nuclear chemistry ; Photochemistry ; Ion ; High-performance liquid chromatography ; Organic chemistry ; Biochemistry ; Optics Carbon and Quantum Dots Applications ; Advanced biosensing and bioanalysis techniques ; Molecular Sensors and Ion Detection
Authors: Piotr M. Kowalski | Zhengda He | Oskar Cheong
Source: Frontiers in Energy Research (article, 2021-03-30)
Field: Materials Science — Materials Chemistry

Electrode and Electrolyte Materials From Atomistic Simulations: Properties of LixFEPO4 Electrode and Zircon-Based Ionic Conductors Li x FePO 4 orthophosphates and fluorite- and pyrochlore-type zirconate materials are widely considered as functional compounds in energy storage devices, either as electrode or solid state electrolyte. These ceramic materials show enhanced cation exchange and anion conductivity properties that makes them attractive for various energy applications. In this contribution we discuss thermodynamic properties of Li x FePO 4 and yttria-stabilized zirconia compounds, including formation enthalpies, stability, and solubility limits. We found that at ambient conditions Li x FePO 4 has a large miscibility gap, which is consistent with existing experimental evidence. We show that cubic zirconia becomes stabilized with Y content of ~8%, which is in line with experimental observations. The computed activation energy of 0.92eV and ionic conductivity for oxygen diffusion in yttria-stabilized zirconia are also in line with the measured data, which shows that atomistic modeling can be applied for accurate prediction of key materials properties. We discuss these results with the existing simulation-based data on these materials produced by our group over the last decade. Last, but not least, we discuss similarities of the considered compounds in considering them as materials for energy storage and radiation damage resistant matrices for immobilization of radionuclides. Materials science ; Electrolyte ; Ionic conductivity ; Ionic bonding ; Conductivity ; Ceramic ; Yttria-stabilized zirconia ; Fast ion conductor ; Cubic zirconia ; Diffusion ; Energy storage ; Electrode ; Chemical engineering ; Inorganic chemistry ; Thermodynamics ; Ion ; Physical chemistry ; Composite material ; Chemistry Nuclear materials and radiation effects ; Radioactive element chemistry and processing ; Zeolite Catalysis and Synthesis