Local premelting about impurities

Latent Representation Learning for Structural Characterization of Catalysts

Supervised machine learning-enabled mapping of the X-ray absorption near edge structure (XANES) spectra to local structural descriptors offers new methods for understanding the structure and function of working nanocatalysts. We briefly summarize a status of XANES analysis approaches by supervised machine learning methods. We present an example of an autoencoder-based, unsupervised machine learning approach for latent representation learning of XANES spectra. This new approach produces a lower-dimensional latent representation, which retains a spectrum-structure relationship that can be eventually mapped to physicochemical properties. The latent space of the autoencoder also provides a pathway to interpret the information content "hidden" in the X-ray absorption coefficient. Our approach (that we named latent space analysis of spectra, or LSAS) is demonstrated for the supported Pd nanoparticle catalyst studied during the formation of Pd hydride. By employing the low-dimensional representation of Pd K-edge XANES, the LSAS method was able to isolate the key factors responsible for the observed spectral changes.

Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy

The knowledge of the coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use an artificial neural network approach to extract the information on the local structure and its in situ changes directly from the x-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic and austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from a body-centered to a face-centered cubic arrangement of iron atoms. This method is attractive for a broad range of materials and experimental conditions.

The Development of Heated Tip Force–Distance Measurements as a Novel Approach to Site-Specific Characterization of Pharmaceutical Materials

The study describes the development of a novel approach to surface analysis whereby thermal probes are used to perform scanning probe microscopy pull-off force measurements as a function of tip rather than sample temperature. The initial impetus for the investigation was the study of a poorly understood phenomenon associated with microthermal analysis (MTA) whereby the thermal probe is pulled into the surface of a sample following temperature-induced softening. Localized thermomechanical analysis experiments were performed on a range of pharmaceutical materials using TA Instruments 2990 Microthermal Analyzer equipped with a TM Microscopes Explorer atomic force microscope. The system was then interfaced with a second instrument to allow simultaneous probe temperature control and pull-off force measurement. It was found that the pull-in effect is due to the adhesion of the probe to the material at elevated (softening) temperatures. However, it was also noted that for paracetamol tablets the pull-off force increased at temperatures well below the softening associated with melting. This behavior was ascribed to surface polymorphic changes caused by the compression process. The temperature-controlled pull-off force method therefore represents a novel and potentially widely applicable means of detecting surface changes that are not easily observed using isothermal pull-off force measurements or indeed standard MTA studies.

Vibrational density of states and Lindemann melting law

We examine the Lindemann melting law at different pressures using the vibrational density of states (DOS), equilibrium melting curve, and Lindemann parameter delta(L) (fractional root-mean-squared displacement, rmsd, at equilibrium melting) calculated independently from molecular dynamics simulations of the Lennard-Jones system. The DOS is obtained using spectra analysis of atomic velocities and accounts for anharmonicity. The increase of delta(L) with pressure is non-negligible: delta(L) is about 0.116 and 0.145 at ambient and extreme pressures, respectively. If the component of rmsd normal to a reflecting plane as in the Debye-Waller-factor-type measurements using x rays is adopted for delta(L), these values are about 0.067 (+/-0.002) and 0.084 (+/-0.003), and are comparable with experimental and calculated values for face-centered-cubic elements. We find that the Lindemann relation holds accurately at ambient and high pressures. The non-negligible pressure dependence of delta(L) suggests that caution should be exerted in applying the Lindemann law to obtaining the high pressure melting curve anchored at ambient pressure.