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A popular heuristic derived from the Kanamori-Goodenough-Anderson rules of superexchange connects bond angles and magnetism in certain transition metal compounds. We evaluate the fulfillment of this heuristic on databases of magnetic structures. The heuristic is partly satisfied in magnetic structures from experiment, and exceptions can be rationalized. We further show that incorporating this heuristic into machine learning models for magnetism improves the prediction.
A streamlined Python-based workflow for transforming Full-Notch Creep Test (FNCT) data into organized, machine-actionable formats is presented. The workflow automates the conversion of raw FNCT data from classic CSV and Excel files into structured outputs that facilitate future semantic integration. Emphasizing practical data handling, the approach includes automation scripts for efficient data extraction, transformation, and storage, which culminate in well-ordered files. This transformation paves the way for potential semantic data integration and facilitates access for users with varying levels of digital experience to enhanced data management in polymer research and testing.
The molecular dynamics of thin films and the adsorbed layer of poly(2-vinylpyridine) (P2VP) were investigated using broadband dielectric spectroscopy (BDS) and spectroscopic ellipsometry. Thin films of P2VP were prepared on silicon substrates and characterized to understand the influence of film thickness on the thermal glass transition temperature (Tg) and molecular mobility. The ellipsometric study revealed a decrease in Tg with decreasing film thickness, attributed to the enhanced mobility at the polymer/air interface. The adsorbed layer, prepared via the solvent leaching approach, exhibited a higher Tg compared to the bulk, indicating reduced molecular mobility due to strong polymer substrate interactions. The dielectric measurements were carried out in two different electrode configurations, crossed electrode capacitors (CEC) and nanostructured electrodes (NSE), where the latter allows for a free surface layer at the polymer/air interface. The relaxation rates of the α-relaxation measured in the CEC geometry collapse into one chart independent from the film thickness. For the thin films measured in the NSE arrangement the relaxation rates slow down with decreasing film thickness which was discussed as related to a stronger interaction of the P2VP segments with the native SiO2 at the surface of the silicon substrate compared to aluminum. It is worth to note that the effect of the enhanced mobility at the polymer/air interface is not observed in the dielectric measurements. BDS measurements in NSE geometry identified an additional relaxation process (α*-relaxation) in thin films, which was more pronounced in the adsorbed layer. This process is hypothesized to be related to molecular fluctuations within the adsorbed layer including the adsorption/desorption dynamics of segments or to a Slow Arrhenius Process (SAP) related to the equilibration dynamics deep in the glassy state.
High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.
The “Metrology for Advanced Hydrogen Storage Solutions” (MefHySto) project is a European initiative addressing the need for large-scale energy storage solutions, that is crucial for the successful transition to renewable energy sources. The main objective of this project was to develop and provide metrological standards and validated techniques for the storage and utilization of hydrogen. Hydrogen is increasingly recognized as an important component in the future energy system due to its ability to store and supply energy during peak demand periods when renewable sources, such as solar and wind, are not generating power.
We introduce a novel adaptive Gaussian Process Regression (GPR) methodology for efficient construction of surrogate models for Bayesian inverse problems with expensive forward model evaluations. An adaptive design strategy focuses on optimizing both the positioning and simulation accuracy of training data in order to reduce the computational cost of simulating training data without compromising the fidelity of the posterior distributions of parameters. The method interleaves a goal-oriented active learning algorithm selecting evaluation points and tolerances based on the expected impact on the Kullback-Leibler divergence of surrogated and true posterior with a Markov Chain Monte Carlo sampling of the posterior. The performance benefit of the adaptive approach is demonstrated for two simple test problems.
In this paper, we demonstrate the value of 1H NMR relaxometry for studying the hydration of clinker-reduced, more climate-friendly cementitious binders. The results were obtained on typical CEM I cements and sister samples containing two different reactive agricultural ashes as well as non-reactive biochars as supplementary cementitious materials. The findings prove that time-resolved NMR measurements provide valuable additional information when combined with classical heat flow calorimetry.
Thin polymer films are of vital importance due to their low production costs and wide range of applications in sensors, electronics, and coatings. Their geometry is ideal for the study of confinement effects, specifically one-dimensional confinement, on the thermodynamic properties and segmental dynamics of polymers. For this investigation, films of PC are prepared on both glass and silica substrates to measure the dielectric and calorimetric behavior as a function of film thickness. The methodology consists of broadband dielectric spectroscopy (BDS), ellipsometry, and atomic force microscopy (AFM). Using ellipsometry, the glass transition shows an increase with decreasing film thickness. Compared to a previous investigation of PC where dilatometry was used, an increase in PC was seen, but now only at thicknesses below 20 nm. Therefore, the critical thickness of PC, where the bulk-like layer no longer percolates through the film, is dependent on the method probing the glass transition. The dielectric behavior shows a deviation from bulk behavior with decreasing film thickness, although still showing a Vogel-Fulcher-Tammann (VFT) temperature dependence for all films. The influence of the adsorbed layer on the molecular mobility was also addressed.
The crack propagation rate of environmental stress cracking was studied on high-density polyethylene compact tension specimens under static loading. Selected environmental liquids are distilled water, 2 wt% aqueous Arkopal N100 solution, and two model liquid mixtures, one based on solvents and one on detergents, representing stress cracking test liquids for commercial crop protection products. The different surface tensions and solubilities, which affect the energetic facilitation of void nucleation and craze development, are studied. Crack growth in surface-active media is strongly accelerated as the solvents induce plasticization, followed by strong blunting significantly retarding both crack initiation and crack propagation. The crack propagation rate for static load as a function of the stress intensity factor within all environments is found to follow the Paris–Erdogan law. Scanning electron micrographs of the fracture surface highlight more pronounced structures with both extensive degrees of plasticization and reduced crack propagation rate, addressing the distinct creep behavior of fibrils. Additionally, the limitations of linear elastic fracture mechanisms for visco-elastic polymers exposed to environmental liquids are discussed.
Colours, nano and surface
(2022)
The basic ideas of colours and pigments are presented. The correlation between nanomaterials and colours are explained. Different methods are presented for investigating nanoparticles and their surface. At the end a case study is presented explaining the importance of coating for the properties of nanoparticles.
