Theoretical X-ray absorption spectroscopy database analysis for oxidised 2D carbon nanomaterials

In this work we provide a proof of principle for a theoretical methodology to identify functionalisation patterns in oxidised carbon 2D nanomaterials. The methodology is based on calculating a large number of X-ray absorption spectra of individually excited carbon atoms in different chemical environments using density functional theory. Since each resulting spectrum gives a fingerprint of the local electronic structure surrounding the excited atom, we may relate each spectrum to the functionalisation pattern of that excited atom up to a desired neighbourhood radius. These functionalisation pattern-specific spectra are collected in a database, that allows fast composition of X-ray absorption spectra for arbitrary structures in density functional theory quality. Finally, we present an exemplary application of the database approach to estimate the relative amount of functional groups in two different experimental samples of carbon nanomaterials

Electron-correlation driven capture and release in double quantum dots

We recently predicted that the interatomic Coulombic electron capture (ICEC) process, a long-range electron correlation driven capture process, is achievable in gated double quantum dots (DQDs). In ICEC an incoming electron is captured by one QD and the excess energy is used to remove an electron from the neighboring QD. In this work we present systematic full three-dimensional electron dynamics calculations in quasi-one dimensional model potentials that allow for a detailed understanding of the connection between the DQD geometry and the reaction probability for the ICEC process. We derive an effective one-dimensional approach and show that its results compare very well with those obtained using the full three-dimensional calculations. This approach substantially reduces the computation times. The investigation of the electronic structure for various DQD geometries for which the ICEC process can take place clarify the origin of its remarkably high probability in the presence of two-electron resonances

Controlled energy-selected electron capture and release in double quantum dots

Highly accurate quantum electron dynamics calculations demonstrate that energy can be efficiently transferred between quantum dots. Specifically, in a double quantum dot an incoming electron is captured by one dot and the excess energy is transferred to the neighboring dot and used to remove an electron from this dot. This process is due to long-range electron correlation and shown to be operative at rather large distances between the dots. The efficiency of the process is greatly enhanced by preparing the double quantum dot such that the incoming electron is initially captured by a two-electron resonance state of the system. In contrast to atoms and molecules in nature, double quantum dots can be manipulated to achieve this enhancement. This mechanism leads to a surprisingly narrow distribution of the energy of the electron removed in the process which is explained by resonance theory. We argue that the process could be exploited in practice.Comment: Lette

Three-Electron Dynamics of the Interparticle Coulombic Decay in Doubly Excited Clusters with One-Dimensional Continuum Confinement

A detailed analysis of the electronic structure and decay dynamics in a symmetric system with three electrons in three linearly aligned binding sites representing quantum dots (QDs) is given. The two outer A QDs are two-level potentials and can act as (virtual) photon emitters, whereas the central B QD can be ionized from its one level into a continuum confined on the QD axis upon absorbing virtual photons in the inter-Coulombic decay (ICD) process. Two scenarios in such an ABA array are explored. One ICD process is from a singly excited resonance state, whose decay releasing one virtual photon we find superimposed with resonance energy transfer among both A QDs. Moreover, the decay-process manifold for a doubly excited (DE) resonance is explored, in which collective ICD among all three sites and excited ICD among the outer QDs engage. Rates for all processes are found to be extremely low, although ICD rates with two neighbors are predicted to double compared to ICD among two sites only. The slowing is caused by Coulomb barriers imposed from ground or excited state electrons in the A sites. Outliers occur on the one hand at short distances, where the charge transfer among QDs mixes the possible decay pathways. On the other hand, we discovered a shape resonance-enhanced DE-ICD pathway, in which an excited and localized B∗ shape resonance state forms, which is able to decay quickly into the final ICD continuum

Hydration Structure of Diamondoids from Reactive Force Fields

Diamondoids are promising materials for applications in catalysis and nanotechnology. Since many of their applications are in aqueous environments, to understand their function it is essential to know the structure and dynamics of the water molecules in their first hydration shells. In this study, we adapt a reactive force field (ReaxFF) for atomistically resolved molecular dynamics simulations of hydrated diamondoids to characterize their interfacial water structure. We parametrize the force field and validate the water structure against geometry-optimized structures from density functional theory. We compare the results to water structures around diamondoids with all partial charges set to zero, and around charged smooth spheres, and find qualitatively similar water structuring in all cases. However, the response of the water molecules is most sensitive to the partial charges in the atomistically resolved diamondoids. From the systematic exclusion of atomistic detail, we can draw generic conclusions about the nature of the hydrophobic effect at nanoparticle interfaces and link it to the interfacial water structure. The interactions between discrete partial charges on short length scales affect the hydration structures strongly, but the hydrophobic effect seems to be stable against these short scale surface perturbations. Our methods and the workflow we present are transferable to other hydrocarbons and interfacial systems

Проект создания умных парковок с применением технологии IoT в системе sharing economy

Целью работы является выявление механизмов организации и создания бизнес-модели проекта умного паркинга с применением технологии IoT в системе экономики совместного потребления. В результате исследования были получены данные о возможности и целесообразности реализации проекта как стартапа, представлен механизм организации и создания бизнес-модели проекта умной парковки с применением технологии IoT в экономике совместного потребления.The aim of the work is to identify mechanisms for organizing and creating a business model for a smart parking project using IoT technology in the shared consumption economy. The study data were obtained on the possibility and feasibility of the project as a startup, presented mechanism for organizing and creating business models project a smart parking using IoT technologies in joint consumption economy

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

The use of sophisticated machine learning (ML) models, such as graph neural networks (GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly. However, ensuring the interpretability of these models’ predictions remains a challenge. For example, a rigorous understanding of the predicted X-ray absorption spectrum (XAS) generated by such ML models requires an in-depth investigation of the respective black-box ML model used. Here, this is done for different GNNs based on a comprehensive, custom-generated XAS data set for small organic molecules. We show that a thorough analysis of the different ML models with respect to the local and global environments considered in each ML model is essential for the selection of an appropriate ML model that allows a robust XAS prediction. Moreover, we employ feature attribution to determine the respective contributions of various atoms in the molecules to the peaks observed in the XAS spectrum. By comparing this peak assignment to the core and virtual orbitals from the quantum chemical calculations underlying our data set, we demonstrate that it is possible to relate the atomic contributions via these orbitals to the XAS spectrum

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra

The use of sophisticated machine learning (ML) models, such as graph neural networks (GNNs), to predict complex molecular properties or all kinds of spectra has grown rapidly. However, ensuring the interpretability of these models’ predictions remains a challenge. For example, a rigorous understanding of the predicted X-ray absorption spectrum (XAS) generated by such ML models requires an in-depth investigation of the respective black-box ML model used. Here, this is done for different GNNs based on a comprehensive, custom-generated XAS data set for small organic molecules. We show that a thorough analysis of the different ML models with respect to the local and global environments considered in each ML model is essential for the selection of an appropriate ML model that allows a robust XAS prediction. Moreover, we employ feature attribution to determine the respective contributions of various atoms in the molecules to the peaks observed in the XAS spectrum. By comparing this peak assignment to the core and virtual orbitals from the quantum chemical calculations underlying our data set, we demonstrate that it is possible to relate the atomic contributions via these orbitals to the XAS spectrum

Combined first-principles statistical mechanics approach to sulfur structure in organic cathode hosts for polymer based lithium–sulfur (Li–S) batteries

Polymer-based batteries that utilize organic electrode materials are considered viable candidates to overcome the common drawbacks of lithium–sulfur (Li–S) batteries. A promising cathode can be developed using a conductive, flexible, and free-standing polymer, poly(4-thiophen-3-yl)benzenethiol) (PTBT), as the sulfur host material. By a vulcanization process, sulfur is embedded into this polymer. Here, we present a combination of electronic structure theory and statistical mechanics to characterize the structure of the initial state of the charged cathode on an atomic level. We perform a stability analysis of differently sulfurized TBT dimers as the basic polymer unit calculated within density-functional theory (DFT) and combine this with a statistical binding model for the binding probability distributions of the vulcanization process. From this, we deduce sulfur chain length (“rank”) distributions and calculate the average sulfur rank depending on the sulfur concentration and temperature. This multi-scale approach allows us to bridge the gap between the local description of the covalent bonding process and the derivation of the macroscopic properties of the cathode. Our calculations show that the main reaction of the vulcanization process leads to high-probability states of sulfur chains cross-linking TBT units belonging to different polymer backbones, with a dominant rank around n = 5. In contrast, the connection of adjacent TBT units of the same polymer backbone by a sulfur chain is the side reaction. These results are experimentally supported by Raman spectroscopy