jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sylvie Neyertz | Saman Salimi | Farzaneh Radmanesh | Nieck E. Benes | David Brown
Source: Physical Chemistry Chemical Physics (article, 2021-01-01)
Field: Materials Science — Polymers and Plastics

High-temperature molecular screening of hybrid polyOAPS-imide networks based on octa(aminophenyl)silsesquioxane for increased thermomechanical resistance A new family of hybrid hyper-cross-linked thin films based on inorganic polyhedral oligomeric silsesquioxane (POSS) cages covalently bound with short organic imides has recently been developed using interfacial polycondensation followed by high-temperature imidization. These polyPOSS-imide networks were aimed at gas separations under harsh conditions, but the aliphatic arms of the initial POSS precursor, octa(aminopropyl)silsesquioxane, were found to be a weak link. This work investigates the replacement of the aliphatic arm by a phenyl derivative, octa(aminophenyl)silsesquioxane (OAPS). Although this new precursor is expected to be more thermoresistant, it introduces extra degrees of complexity since the functional -NH2 group on the phenyl ring can either be attached at a meta, a para or an ortho position. In order to avoid a costly programme of synthesis and testing, molecular dynamics (MD) simulations have been used to efficiently screen a large number of candidate structures based on mixtures of the three OAPS isomers, the initial POSS and three organic precursors, the PMDA, 6FDA and ODPA dianhydrides. Following cross-linking at room temperature, twenty-two model networks were further relaxed at the imidization temperature and directly tested under harsh conditions at 300 °C. The screening stage included the characterization of their intercage single-links and double-links, which reinforce the structures, and intracage links, which have the opposite effect. Carrying out the cross-linking reactions to completion significantly improved the resistance to isotropic dilation. The initial POSS as well as the flexible 6FDA and ODPA linkers were found to be prone to large deformations, whereas the orthoOAPS, metaOAPS, paraOAPS and the PMDA linker prevented volume dilations. Upon uniaxial tension, the Young's moduli varied in the order paraOAPS < POSS ≈ metaOAPS < orthoOAPS for the inorganic precursors and in the order 6FDA < ODPA < PMDA for the organic precursors. In all cases, the networks based on either orthoOAPS and/or PMDA displayed superior resistance. Nine polyOAPS-imides were further heated up to 400 °C, i.e. closer to the expected degradation, and re-submitted to isotropic dilations and uniaxial tensions. They confirmed the trends found at 300 °C with no signs of structural collapse. Using OAPS as the inorganic precursor thus significantly reinforces the thermoresistance of these hybrid hyper-cross-linked networks. Imide ; Silsesquioxane ; Materials science ; Polymer chemistry ; Composite material ; Polymer Synthesis and properties of polymers ; Silicone and Siloxane Chemistry ; Advanced ceramic materials synthesis
Authors: Miroslav Šlouf | Radim Skoupý | Ewa Pavlová | Vladislav Krzyžánek
Source: Materials (article, 2021-12-09)
Field: Materials Science — Surfaces, Coatings and Films

High Resolution Powder Electron Diffraction in Scanning Electron Microscopy A modern scanning electron microscope equipped with a pixelated detector of transmitted electrons can record a four-dimensional (4D) dataset containing a two-dimensional (2D) array of 2D nanobeam electron diffraction patterns; this is known as a four-dimensional scanning transmission electron microscopy (4D-STEM). In this work, we introduce a new version of our method called 4D-STEM/PNBD (powder nanobeam diffraction), which yields high-resolution powder diffractograms, whose quality is fully comparable to standard TEM/SAED (selected-area electron diffraction) patterns. Our method converts a complex 4D-STEM dataset measured on a nanocrystalline material to a single 2D powder electron diffractogram, which is easy to process with standard software. The original version of 4D-STEM/PNBD method, which suffered from low resolution, was improved in three important areas: (i) an optimized data collection protocol enables the experimental determination of the point spread function (PSF) of the primary electron beam, (ii) an improved data processing combines an entropy-based filtering of the whole dataset with a PSF-deconvolution of the individual 2D diffractograms and (iii) completely re-written software automates all calculations and requires just a minimal user input. The new method was applied to Au, TbF<sub>3</sub> and TiO<sub>2</sub> nanocrystals and the resolution of the 4D-STEM/PNBD diffractograms was even slightly better than that of TEM/SAED. Selected area diffraction ; Reflection high-energy electron diffraction ; Scanning transmission electron microscopy ; Materials science ; Scanning electron microscope ; High-resolution transmission electron microscopy ; Optics ; Electron diffraction ; Diffraction ; Powder diffraction ; Nanocrystalline material ; Resolution (logic) ; Energy filtered transmission electron microscopy ; Conventional transmission electron microscope ; Transmission electron microscopy ; Electron backscatter diffraction ; Scanning confocal electron microscopy ; Crystallography ; Nanotechnology ; Physics ; Chemistry ; Computer science ; Artificial intelligence Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; X-ray Diffraction in Crystallography
Authors: Daniela Schönenbach | Felix Berg | Markus Breckheimer | Daniel Hagenlocher | Pascal Schönberg | R. Haas | Samer Amayri | Tobias Reich
Source: Analytical and Bioanalytical Chemistry (article, 2021-05-10)
Field: Chemistry — Inorganic Chemistry

Development, characterization, and first application of a resonant laser secondary neutral mass spectrometry setup for the research of plutonium in the context of long-term nuclear waste storage Plutonium is a major contributor to the radiotoxicity in a long-term nuclear waste repository; therefore, many studies have focused on interactions of plutonium with the technical, geotechnical, and geological barriers of a possible nuclear waste storage site. In order to gain new insights into the sorption on surfaces and diffusion of actinides through these complex heterogeneous materials, a highly sensitive method with spatial resolution is required. Resonant laser secondary neutral mass spectrometry (Laser-SNMS) uses the spatial resolution available in time-of-flight secondary ion mass spectrometry (TOF-SIMS) in combination with the high selectivity, sensitivity, and low background noise of resonance ionization mass spectrometry (RIMS) and is, therefore, a promising method for the study and analysis of the geochemical behavior of plutonium in long-term nuclear waste storage. The authors present an approach with a combined setup consisting of a commercial TOF-SIMS instrument and a Ti:sapphire (Ti:Sa) laser system, as well as its optimization, characterization, and improvements compared to the original proof of concept by Erdmann et al. (2009). As a first application, the spatial distributions of plutonium and other elements on the surface of a pyrite particle and a cement thin section were measured by Laser-SNMS and TOF-SIMS, respectively. These results exemplify the potential of these techniques for the surface analysis of heterogeneous materials in the context of nuclear safety research. Plutonium ; Context (archaeology) ; Radioactive waste ; Secondary ion mass spectrometry ; Mass spectrometry ; Accelerator mass spectrometry ; Chemistry ; Characterization (materials science) ; Transuranium element ; Laser ; Analytical Chemistry (journal) ; Radiochemistry ; Nuclear engineering ; Materials science ; Nanotechnology ; Nuclear chemistry ; Physics ; Geology ; Environmental chemistry ; Optics ; Engineering Radioactive element chemistry and processing ; Ion-surface interactions and analysis ; Radioactive contamination and transfer
Authors: Johannes C. Hermann | Daniel Bischoff | Phillip Grob | Robert Janowski | D. Hekmat | Dierk Niessing | Martin Zacharias | Dirk Weuster‐Botz
Source: Crystals (article, 2021-05-24)
Field: Materials Science — Materials Chemistry

Controlling Protein Crystallization by Free Energy Guided Design of Interactions at Crystal Contacts Protein crystallization can function as an effective method for protein purification or formulation. Such an application requires a comprehensive understanding of the intermolecular protein–protein interactions that drive and stabilize protein crystal formation to ensure a reproducible process. Using alcohol dehydrogenase from Lactobacillus brevis (LbADH) as a model system, we probed in our combined experimental and computational study the effect of residue substitutions at the protein crystal contacts on the crystallizability and the contact stability. Increased or decreased contact stability was calculated using molecular dynamics (MD) free energy simulations and showed excellent qualitative correlation with experimentally determined increased or decreased crystallizability. The MD simulations allowed us to trace back the changes to their physical origins at the atomic level. Engineered charge–charge interactions as well as engineered hydrophobic effects could be characterized and were found to improve crystallizability. For example, the simulations revealed a redesigning of a water mediated electrostatic interaction (“wet contact”) into a water depleted hydrophobic effect (“dry contact”) and the optimization of a weak hydrogen bonding contact towards a strong one. These findings explained the experimentally found improved crystallizability. Our study emphasizes that it is difficult to derive simple rules for engineering crystallizability but that free energy simulations could be a very useful tool for understanding the contribution of crystal contacts for stability and furthermore could help guide protein engineering strategies to enhance crystallization for technical purposes. Crystallization ; Protein crystallization ; Molecular dynamics ; Chemical physics ; Materials science ; Electrostatics ; Contact angle ; Electrostatic interaction ; Intermolecular force ; Crystal (programming language) ; Chemistry ; Crystallography ; Thermodynamics ; Computational chemistry ; Physics ; Physical chemistry ; Computer science ; Molecule Enzyme Structure and Function ; Protein Structure and Dynamics ; Crystallization and Solubility Studies
Authors: Anna V. Paterova | Dmitry Kalashnikov | Egor Khaidarov | Hongzhi Yang | Tobias W. W. Maß | Ramón Paniagua‐Domínguez | Arseniy I. Kuznetsov | Leonid A. Krivitsky
Source: SHILAP Revista de lepidopterología (article, 2021-03-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Non-linear interferometry with infrared metasurfaces The optical elements comprised of sub-diffractive light scatterers, or metasurfaces, hold a promise to reduce the footprint and unfold new functionalities of optical devices. A particular interest is focused on metasurfaces for manipulation of phase and amplitude of light beams. Characterisation of metasurfaces can be performed using interferometry, which, however, may be cumbersome, specifically in the infrared (IR) range. Here, we realise a new method for characterising metasurfaces operating in the telecom IR range using accessible components for visible light. Correlated IR and visible photons are launched into a non-linear interferometer so that the phase profile, imposed by the metasurface on the IR photons, modifies the interference at the visible photon wavelength. Furthermore, we show that this concept can be used for broadband manipulation of the intensity profile of a visible beam using a single IR metasurface. Our method unfolds the potential of quantum interferometry for the characterization of advanced optical elements. Interferometry ; Optics ; Infrared ; Photon ; Interference (communication) ; Optoelectronics ; Broadband ; Visible spectrum ; Physics ; Phase (matter) ; Astronomical interferometer ; Computer science ; Telecommunications Metamaterials and Metasurfaces Applications ; Random lasers and scattering media ; Orbital Angular Momentum in Optics
Authors: Philipp Merkl | Chaw‐Keong Yong | Marlene Liebich | Isabella Hofmeister | Gunnar Berghäuser | Ermin Malić | R. Huber
Source: Nature Communications (article, 2021-03-19)
Field: Materials Science — Materials Chemistry

Proximity control of interlayer exciton-phonon hybridization in van der Waals heterostructures Van der Waals stacking has provided unprecedented flexibility in shaping many-body interactions by controlling electronic quantum confinement and orbital overlap. Theory has predicted that also electron-phonon coupling critically influences the quantum ground state of low-dimensional systems. Here we introduce proximity-controlled strong-coupling between Coulomb correlations and lattice dynamics in neighbouring van der Waals materials, creating new electrically neutral hybrid eigenmodes. Specifically, we explore how the internal orbital 1s-2p transition of Coulomb-bound electron-hole pairs in monolayer tungsten diselenide resonantly hybridizes with lattice vibrations of a polar capping layer of gypsum, giving rise to exciton-phonon mixed eigenmodes, called excitonic Lyman polarons. Tuning orbital exciton resonances across the vibrational resonances, we observe distinct anticrossing and polarons with adjustable exciton and phonon compositions. Such proximity-induced hybridization can be further controlled by quantum designing the spatial wavefunction overlap of excitons and phonons, providing a promising new strategy to engineer novel ground states of two-dimensional systems. Condensed matter physics ; Exciton ; Phonon ; van der Waals force ; Physics ; Polaron ; Electron ; Heterojunction ; Quantum mechanics 2D Materials and Applications ; Perovskite Materials and Applications ; Topological Materials and Phenomena
Authors: Zhuo Bin Siu | M. B. A. Jalil
Source: Scientific Reports (article, 2021-04-07)
Field: Materials Science — Materials Chemistry

Effective Hamiltonian for silicene under arbitrary strain from multi-orbital basis A tight-binding (TB) Hamiltonian is derived for strained silicene from a multi-orbital basis. The derivation is based on the Slater-Koster coupling parameters between different orbitals across the silicene lattice and takes into account arbitrary distortion of the lattice under strain, as well as the first and second-order spin-orbit interactions (SOI). The breaking of the lattice symmetry reveals additional SOI terms which were previously neglected. As an exemplary application, we apply the linearized low-energy TB Hamiltonian to model the current-induced spin accumulation in strained silicene coupled to an in-plane magnetization. The interplay between symmetry-breaking and the additional SOI terms induces an out-of-plane spin accumulation. This spin accumulation remains unbalanced after summing over the Fermi surfaces of the occupied bands and the two valleys, and can thus be utilized for spin torque switching. Silicene ; Condensed matter physics ; Hamiltonian (control theory) ; Physics ; Atomic orbital ; Lattice (music) ; Spin–orbit interaction ; Symmetry breaking ; Fermi energy ; Quantum mechanics ; Graphene ; Mathematics ; Electron Graphene research and applications ; Topological Materials and Phenomena ; 2D Materials and Applications
Authors: Arjan Burema | T. Banerjee
Source: Applied Physics Letters (article, 2021-07-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Temperature-dependent periodicity halving of the in-plane angular magnetoresistance in La0.67Sr0.33MnO3 thin films on LaAlO3 Strain-engineering is used as a tool to alter electronic and magnetic properties like anisotropy energy. This study reports the different angle-dependent magnetoresistance properties of the strain-engineered La0.67Sr0.33MnO3 (LSMO) thin films, grown on LaAlO3, compared to their bulk analogs. Upon increasing temperature, a symmetry change from fourfold [cos(4θ)] to twofold [cos(2θ)] is observed in the angle-dependent resistance measurements. This systematic study with increasing temperature allows us to define three distinct temperature-dependent phases. The fourfold symmetric signal originates from magnetocrystalline anisotropy, whereas the twofold symmetric signal is believed to be the conventional anisotropic magnetoresistance. Our observations show that strain-engineering creates the possibility to manipulate the anisotropy, which, for example, can ultimately lead to observations of noncollinear quasi-particles like skyrmions in single layer thin films of LSMO. Magnetoresistance ; Condensed matter physics ; Anisotropy ; Magnetocrystalline anisotropy ; Thin film ; Materials science ; Colossal magnetoresistance ; Anisotropy energy ; Magnetic anisotropy ; Strain engineering ; Magnetization ; Physics ; Nanotechnology ; Optics ; Magnetic field ; Phase transition Magnetic and transport properties of perovskites and related materials ; Advanced Condensed Matter Physics ; Electronic and Structural Properties of Oxides
Authors: Robert Spiers | John H. Kalivas
Source: Journal of Chemical Information and Modeling (article, 2021-04-26)
Field: Chemistry — Analytical Chemistry

Reliable Model Selection without Reference Values by Utilizing Model Diversity with Prediction Similarity Predictive modeling (calibration or training) with various data formats, such as near-infrared (NIR) spectra and quantitative structure-activity relationship (QSAR) data, provides essential information if a proper model is selected. Similarly, with a general model selection approach, spectral model maintenance (updating) from original modeling conditions to new conditions can be performed for dynamic modeling. Fundamental modeling (partial least-squares (PLS) and others) and maintenance processes (domain adaptation or transfer learning and others) require selection of tuning parameter(s) values to isolate models that can accurately predict new samples or molecules, e.g., number of PLS latent variables to predict analyte concentration. Regardless of the modeling task, model selection is complex and without a reliable protocol. Tuning parameter selection typically depends on only one model quality measure assessing model bias using prediction accuracy. Developed in this paper is a generic model selection process using concepts from consensus modeling and QSAR activity landscapes. It is a consensus filtering approach that prioritizes model diversity (MD) while conserving prediction similarity (PS) fused with a common bias-variance trade-off measure. A significant feature of MDPS is that a cross-validation scheme is not needed because models are selected relative to predicting new samples or molecules, i.e., model selection uses unlabeled samples (without reference values) for active predictions. The versatility and reliability of MDPS model selection is shown using four NIR data sets and a QSAR data set. The study also substantiates the Rashomon effect where there is not one best model tuning parameter value that provides accurate predictions. Model selection ; Computer science ; Applicability domain ; Selection (genetic algorithm) ; Similarity (geometry) ; Quantitative structure–activity relationship ; Set (abstract data type) ; Data mining ; Calibration ; Partial least squares regression ; Artificial intelligence ; Feature selection ; Machine learning ; Mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Pesticide Residue Analysis and Safety
Authors: Dilek Yıldız
Source: Atomic Spectroscopy (article, 2021-05-27)
Field: Chemistry — Analytical Chemistry

Determination Of Selenium By Platinum-Coated Tungsten Coil Trap Hydride Generation-Atomic Absorption Spectrometry A highly sensitive analytical technique was developed in which gaseous hydrogen selenide generated by sodium tetrahydroborate reduction was transported and trapped on a resistively heated platinum-coated W-coil trap for in situ preconcentration. The selenium concentration was determined using hydride generation-atomic absorption spectrometry (HG-AAS). The surface of the W-coil was covered with platinum using the electrodeposition technique in the presence of H2 and Ar. According to the results of Scanning Electron Microscopy and Energy Dispersive X-ray Spectroscopy (SEM-EDX) images, the ratio of Pt was 54.74% on the W-coil trap surface. Various experimental conditions, such NaBH 4 and hydrochloric acid concentration, and carrier gas flow rate, were optimized. In addition, the effect of the hydride-forming elements was quantitatively evaluated. The limit of detection for Se was 21.1 ng/L. The proposed method was also applied to the determination of selenium in certified reference material (SRM 1640a Trace Elements in Natural Water) which showed that the analysis could be performed with a relative error of about 8%. The precision of the method was evaluated and a relative standard deviation (%RSD) lower than 10% was obtained. Chemistry ; Selenium ; Hydride ; Atomic absorption spectroscopy ; Tungsten ; Analytical Chemistry (journal) ; Platinum ; Mass spectrometry ; Radiochemistry ; Metal ; Environmental chemistry ; Chromatography Analytical chemistry methods development
Authors: Egnonnumi Codjo | Bashir Bakhshideh Zad | Jean‐François Toubeau | Bruno François | François Vallée
Source: Energies (article, 2021-05-15)
Field: Materials Science — Materials Chemistry

Machine Learning-Based Classification of Electrical Low Voltage Cable Degradation Low voltage distribution networks have not been traditionally designed to accommodate the large-scale integration of decentralized photovoltaic (PV) generations. The bidirectional power flows in existing networks resulting from the load demand and PV generation changes as well as the influence of ambient temperature led to voltage variations and increased the leakage current through the cable insulation. In this paper, a machine learning-based framework is implemented for the identification of cable degradation by using data from deployed smart meter (SM) measurements. Nodal voltage variations are supposed to be related to cable conditions (reduction of cable insulation thickness due to insulation wear) and to client net demand changes. Various machine learning techniques are applied for classification of nodal voltages according to the cable insulation conditions. Once trained according to the comprehensive generated datasets, the implemented techniques can classify new network operating points into a healthy or degraded cable condition with high accuracy in their predictions. The simulation results reveal that logistic regression and decision tree algorithms lead to a better prediction (with a 97.9% and 99.9% accuracy, respectively) result than the k-nearest neighbors (which reach only 76.7%). The proposed framework offers promising perspectives for the early identification of LV cable conditions by using SM measurements. Smart meter ; Decision tree ; Voltage ; Power cable ; Photovoltaic system ; Identification (biology) ; Computer science ; Electronic engineering ; Smart grid ; Engineering ; Electrical engineering ; Automotive engineering ; Machine learning ; Materials science High voltage insulation and dielectric phenomena ; Power System Reliability and Maintenance ; Electricity Theft Detection Techniques