Ti-based molecules and materials are ubiquitous and play a major role in both homogeneous and heterogeneous catalytic processes. Understanding the electronic structures of their active sites ...(oxidation state, local symmetry, and ligand environment) is key to developing molecular-level structure-property relationships. In that context, X-ray absorption spectroscopy (XAS) offers a unique combination of elemental selectivity and sensitivity to local symmetry. Commonly, for early transition metals such as Ti, K-edge XAS is applied for in situ characterization and subsequent structural analysis with high sensitivity toward tetrahedral species. Ti L
-edge spectroscopy is in principle complementary and offers specific opportunities to interrogate the electronic structure of five-and six-coordinated species. It is, however, much more rarely implemented because the use of soft X-rays implies ultrahigh vacuum conditions. Furthermore, the interpretation of the data can be challenging. Here, we show how Ti L
-edge spectroscopy can help to obtain unique information about both homogeneous and heterogeneous epoxidation catalysts and develop a molecular-level relationship between spectroscopic signatures and electronic structures. Toward this goal, we first establish a spectral library of molecular Ti reference compounds, comprising various coordination environments with mono- and dimeric Ti species having O, N, and Cl ligands. We next implemented a computational methodology based on multiplet ligand field theory and maximally localized Wannier orbitals benchmarked on our library to understand Ti L
-edge spectroscopic signatures. We finally used this approach to track and predict the spectra of catalytically relevant intermediates, focusing on Ti-based olefin epoxidation catalysts.
Full text
Available for:
IJS, KILJ, NUK, PNG, UL, UM
Gold nanoparticles represent an important class of functional nanomaterials for optoelectronics, biomedical applications, and catalysis. Therefore, controllable synthesis of nanoparticles with ...specified size and shape is important. Though reduction of gold ions is quite a simple process and may be performed with many different protocols, the reproducibility of the results and transfer of protocols between independent research groups remains a challenging task. Machine learning analysis based on statistical approaches is hardly applicable to the published data, since most of the researchers report only successful syntheses. In this work, we apply uniform sampling of the reaction parameter space. The concentrations of gold precursor, reducing agent, and surfactant were varied via an improved Latin hypercube sampling, and each run was performed under in situ UV–vis control. Based on the resulting set of optical spectra, we address the relevant chemical questions about nanoparticle formation, their shape, and period of growth. Our work demonstrates a data driven approach applied to the space of reaction parameters in a limited available set of experiments.
Full text
Available for:
IJS, KILJ, NUK, PNG, UL, UM
Branded apps have attracted an increasing amount of attention as a marketing communication platform. With branded apps, companies try to create value for their brands among prospective and current ...customers by providing entertainment and information content. The aim of this study was to examine a) whether branded apps influence consumers' cognitive and affective brand responses, b) whether this effect is moderated by the type of branded app (i.e., information vs. entertainment), and c) to what extent enjoyment and elaboration are explanatory mechanisms for these effects. An experiment demonstrated that 1) branded apps enhanced brand responses, 2) an entertainment app evoked higher levels of enjoyment, which in turn enhanced affective brand responses, and 3) an informational app evoked higher levels of elaboration, which enhanced cognitive brand responses. Theoretical and practical implications for branded app designers and mobile advertisers are discussed.
•Entertainment branded apps enhance brand attitude and brand relationship.•App enjoyment explains persuasion effects of entertainment branded apps.•Information branded apps enhance cognitive brand responses.•Cognitive elaboration explains persuasion effects of information branded apps.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Ab initio simulations of the pre-edge XAS spectra and other related resonance spectroscopies require taking into account 3d-4p hybridization on the 3d metal site. While the hybridization Hamiltonian ...could be parameterized on the basis of the symmetry of the system we introduce instead a set of 4p orbitals directly within the local Hamiltonian of the multiplet ligand-field approach. The maximally localized Wannier orbitals and 3d-4p hoppings are calculated then on the basis of band structure and total potential of the system. We show applicability of the method on the Fe3O4 structure with the Fe ions in different coordination and charge state in a single unit cell.
•p-d hybridization parameters were included ab initio in the MLFT Hamiltonian.•Method correctly reproduces pre-edge XAS spectra for the systems containing several inequivalent sites in the unit cell.•Quantitative analysis of the pre-edge HERFD XAS revealed oxidation of 8 nm Fe3O4 nanoparticles.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The results of studying the stability of high-entropy NbTiHfVZr alloy on the basis of analysis of (i) the critical Hume-Rothery parameters, (ii) the enthalpy of binary alloys by the Miedema method, ...and (iii) the mixing entropy of NbTiHfVZr alloy near the melting point are presented. The temperature stability regions extending from the melting point to 1200 K for NbTiHfVZr alloy have been revealed by the method of inverse hull webs. In the case of NbTiHfZr, the temperature stability region extends up to the room temperature. The obtained results evidence that NbTiHfVZr and NbTiHfZr can be classified as high-entropy alloys, whose lattices belong to the class of single-phase one-element solid solutions. It has been established by the Rietveld method on the basis of an experimental X-ray diffraction pattern that the cubic HfNbTiVZr, Hf
2
Nb
2
Ti
2
V
2
Zr
2
, NbHfTiZr, and Hf
2
Nb
2
Ti
2
Zr
2
lattices found by the USPEX code with space group
P
1 make a predominant contribution to the integral intensity. In this study, the full structural information including unit cell lattice parameters, atomic coordinates, space group, population of sites, etc. has been established for the HfNbTiVZr, Hf
2
Nb
2
Ti
2
V
2
Zr
2
, NbHfTiZr, and Hf
2
Nb
2
Ti
2
Zr
2
cubic lattices. The mentioned alloys are stable and characterized by a high bound energy and, according to the found room-temperature elasticity moduli, belong to high-strength materials. The cubic HfNbTiVZr, Hf
2
Nb
2
Ti
2
V
2
Zr
2
, NbHfTiZr, and Hf
2
Nb
2
Ti
2
Zr
2
lattices can be incorporated into the crystallographic database used to identify the structural state of high-entropy NbTiHfZr and NbTiHfVZr alloys.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
16.
Development of a ReaxFF potential for Au–Pd Rusalev, Yu V; Motseyko, A V; Guda, A A ...
Journal of physics. Condensed matter,
2022-Dec-14, Volume:
35, Issue:
6
Journal Article
Peer reviewed
The bimetallic alloys often outperform their single-component counterparts due to synergistic effects. Being widely known, the Au-Pd alloy is a promising candidate for the novel heterogeneous ...nanocatalysts. Rational design of such systems requires theoretical simulations under ambient conditions.
quantum-mechanical calculations employ the density functional theory (DFT) and are limited to the systems with few tens of atoms and short timescales. The alternative solution implies development of reliable atomistic potentials. Among different approaches ReaxFF combines chemical accuracy and low computational costs. However, the development of a new potential is a problem without unique solution and thus requires accurate validation criteria. In this work we construct ReaxFF potential for the Au-Pd system based on
DFT calculations for bulk structures, slabs and nanoparticles with different stoichiometry. The validation was performed with molecular dynamics and Monte-Carlo calculations. We present several optimal parametrizations that describe experimental bulk mechanical and thermal properties, atomic order-disorder phase transition temperatures and the resulting ordered crystal structures.
Microscopic tissue analysis is the key diagnostic method needed for disease identification and choosing the best treatment regimen. According to the Global Cancer Observatory, approximately two ...million people are diagnosed with colorectal cancer each year, and an accurate diagnosis requires a significant amount of time and a highly qualified pathologist to decrease the high mortality rate. Recent development of artificial intelligence technologies and scanning microscopy introduced digital pathology into the field of cancer diagnosis by means of the whole-slide image (WSI). In this work, we applied deep learning methods to diagnose six types of colon mucosal lesions using convolutional neural networks (CNNs). As a result, an algorithm for the automatic segmentation of WSIs of colon biopsies was developed, implementing pre-trained, deep convolutional neural networks of the ResNet and EfficientNet architectures. We compared the classical method and one-cycle policy for CNN training and applied both multi-class and multi-label approaches to solve the classification problem. The multi-label approach was superior because some WSI patches may belong to several classes at once or to none of them. Using the standard one-vs-rest approach, we trained multiple binary classifiers. They achieved the receiver operator curve AUC in the range of 0.80–0.96. Other metrics were also calculated, such as accuracy, precision, sensitivity, specificity, negative predictive value, and F1-score. Obtained CNNs can support human pathologists in the diagnostic process and can be extended to other cancers after adding a sufficient amount of labeled data.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Ti-based molecules and materials are ubiquitous and play a major role in both homogeneous and heterogeneous catalytic processes. Understanding the electronic structures of their active sites ...(oxidation state, local symmetry, and ligand environment) is key to developing molecular-level structure–property relationships. In that context, X-ray absorption spectroscopy (XAS) offers a unique combination of elemental selectivity and sensitivity to local symmetry. Commonly, for early transition metals such as Ti, K-edge XAS is applied for in situ characterization and subsequent structural analysis with high sensitivity toward tetrahedral species. Ti L2,3-edge spectroscopy is in principle complementary and offers specific opportunities to interrogate the electronic structure of five-and six-coordinated species. It is, however, much more rarely implemented because the use of soft X-rays implies ultrahigh vacuum conditions. Furthermore, the interpretation of the data can be challenging. Here, we show how Ti L2,3-edge spectroscopy can help to obtain unique information about both homogeneous and heterogeneous epoxidation catalysts and develop a molecular-level relationship between spectroscopic signatures and electronic structures. Toward this goal, we first establish a spectral library of molecular Ti reference compounds, comprising various coordination environments with mono- and dimeric Ti species having O, N, and Cl ligands. We next implemented a computational methodology based on multiplet ligand field theory and maximally localized Wannier orbitals benchmarked on our library to understand Ti L2,3-edge spectroscopic signatures. We finally used this approach to track and predict the spectra of catalytically relevant intermediates, focusing on Ti-based olefin epoxidation catalysts.
Full text
Available for:
IJS, KILJ, NUK, PNG, UL, UM
Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between ...elementary processes: adsorption, activation, desorption, and reaction. These processes, in turn, depend on the inlet gas composition, temperature, and pressure. At a steady state, the active surface sites may be inaccessible due to adsorbed reagents. Periodic regime may thus improve the yield, but the appropriate period and waveform are not known in advance. Dynamic control should account for surface and atmospheric modifications and adjust reaction parameters according to the current state of the system and its history. In this work, we applied a reinforcement learning algorithm to control CO oxidation on a palladium catalyst. The policy gradient algorithm was trained in the theoretical environment, parametrized from experimental data. The algorithm learned to maximize the CO2 formation rate based on CO and O2 partial pressures for several successive time steps. Within a unified approach, we found optimal stationary, periodic, and nonperiodic regimes for different problem formulations and gained insight into why the dynamic regime can be preferential. In general, this work contributes to the task of popularizing the reinforcement learning approach in the field of catalytic science.
Full text
Available for:
IJS, KILJ, NUK, PNG, UL, UM, UPUK
•Database of direct current magnetron sputtered TiN coatings was compiled.•Machine learning algorithms were trained to predict coating hardness.•Data filtering and imputing improved performance of ...machine learning algorithms.•The most important descriptors for predicting coating hardness were determined.•Trained algorithm was applied for the inverse problem of coating deposition.
Modern vacuum ion-plasma technology makes it possible to obtain coatings of various compositions and properties on the surface of metals. Titanium nitride ion-plasma coatings are the most widely used in industry and can significantly improve the mechanical and tribological characteristics of the tribocontacts. The synthesis of coating depends on many parameters and often an optimized set of parameters from a one coater cannot be directly transferred to another. In this work we have compiled a database of reactive direct current magnetron sputtered TiN coatings based on a wide range of reports available in literature. Machine learning algorithms were trained on the database entries from independent authors to establish a relationship between coating hardness and experimental deposition settings. We address the necessary steps for its training: filtration, imputing and feature selection. The algorithm was then applied to the coating inverse design problem and predicted optimal synthesis parameters for given hardness.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
PDF
