2,374 research outputs found

    Predicted Optimal Bifunctional Electrocatalysts for the Hydrogen Evolution Reaction and the Oxygen Evolution Reaction Using Chalcogenide Heterostructures Based on Machine Learning Analysis of in Silico Quantum Mechanics Based High Throughput Screening

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    Two-dimensional van der Waals heterostructure materials, particularly transition metal dichalcogenides (TMDC), have proved to be excellent photoabsorbers for solar radiation, but performance for such electrocatalysis processes as water splitting to form H₂ and O₂ is not adequate. We propose that dramatically improved performance may be achieved by combining two independent TMDC while optimizing such descriptors as rotational angle, bond length, distance between layers, and the ratio of the bandgaps of two component materials. In this paper we apply the least absolute shrinkage and selection operator (LASSO) process of artificial intelligence incorporating these descriptors together with quantum mechanics (density functional theory) to predict novel structures with predicted superior performance. Our predicted best system is MoTe₂/WTe₂ with a rotation of 300°, which is predicted to have an overpotential of 0.03 V for HER and 0.17 V for OER, dramatically improved over current electrocatalysts for water splitting

    Structure and Catalytic Properties of Ultra-Small Ceria Nanoparticles

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    Cerium dioxide (ceria) is an excellent catalytic material due to its ability to both facilitate oxidation/reduction reactions as well as store/release oxygen as an oxygen buffer. The traditional approach to assess and improve ceria\u27s catalytic behavior focuses on how efficiently O-vacancies can be generated and/or annihilated within the material, and how to extend established understandings of bulk ceria to further explain the greatly enhanced catalytic behavior of ultra-small ceria nanoparticles (uCNPs) with sizes less than 10 nm. Here, using density functional theory (DFT) calculations, we reexamine the atomic and electronic structures of uCNPs, especially their surface configurations. A unique picture dissimilar to the traditional point of view emerges from these calculations for the surface structure of uCNPs. uCNPs similar to those obtained by experimental synthesis and applied in catalytic environments exhibit core-shell like structures overall, with under-stoichiometric, reduced CNP cores and over-stoichiometric, oxidized surface shell constituted by various surface functional groups, e.g.,-Ox and/or -OH surface groups. Therefore, their catalytic behavior is dominated by surface chemistry rather than O-vacancies. Based on this finding, reaction pathways of two prevalent catalytic reactions, namely CO oxidation and the water-gas shift reaction over uCNPs are systematically investigated. Combined, these results demonstrate an alternative understanding of the surface structure of uCNPs, and provide new avenues to explore and enhance their catalytic behavior, which is likely applicable to other transition metal oxide nanoparticles with multivalent ions and very small sizes

    A global optimization approach for searching low energy conformations of proteins

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    De novo protein structure prediction and understanding the protein folding mechanism is an outstanding challenge of Biological Physics. Relying on the thermodynamic hypothesis of protein folding it is expected that the native state of a protein can be found out if the global minimum of the free energy surface is found. To understand the energy landscape or the free energy surface is challenging. The structure and dynamics of proteins are the manifestations of the underlying potential energy surface. Here the potential energy function stands on a framework of all-atom representation and uses purely physics-based interactions. For the solvated proteins the effective free energy is defined as an implicit solvation model which includes the solvation free energy, along with a standard all-atom biomolecular forcefield. A major challenge is to search for the global minimum on this effective free energy surface. In this work the Minima Hopping Algorithm (MHOP) to find global minima on potential energy surfaces has been used for protein structure prediction or in general finding the lowest energy conformations of proteins. Here proteins have been studied both in vacuo and in the aqueous medium. For short peptides starting from a completely extended conformation we could find conformational minima which are very close to the experimentally observed structures

    Theoretical methods for studying charge and spin separation in excited states of large molecules and condensed phase

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    In recent years the GW/BSE approach as a sophisticated many-body method gained considerable attention for ab-initio calculations of a range of properties in finite and infinite systems. For instance, several benchmarks exist for ionization potentials, electron affinities, (band) gaps, and electronically excited states demonstrating an overall good performance of the GW/BSE approach at a computational cost comparable to time-dependent density functional theory (TD-DFT) which is a widely applied method in quantum chemistry. The GW/BSE method outperforms TD-DFT for accurate description of charge-transfer states due to explicit capture of non-local electron-hole interaction mediated by the screened Coulomb potential W(r,r,omega)W(r,r^{'},omega). Furthermore, dynamical correlation is properly described through explicit frequency dependency of W(r,r,omega)W(r,r^{'},omega). Long-range dispersion effects are accounted for by infinite summation of non-local electron correlation contributions; the so-called ring diagrams within the random-phase approximation (RPA). Therefore, the GW/BSE method provides a reliable theoretical tool with a satisfactory prediction power for electronic and optical properties of materials at different phases, and hence is consistently used in this thesis for different types of problems. In the first part of this thesis, the effect of electron-electron correlation, electron-phonon coupling and vertex corrections on the electronic band structure of ice and liquid water within the many-body Green's function formalism (the GW method) is investigated. Furthermore, within the same methodology and based on the Bethe-Salpeter equation (BSE) linear optical absorption spectra of antiferromagnetic zinc ferrite, water and ammonia in the condensed phase are calculated and analyzed in detail. Here, the electron-hole correlation which is responsible for the observed red-shift of absorption peaks and spectral weight redistributions is explicitly taken into account. The electron-hole effects are also of extreme importance for the non-linear absorption spectrum of liquid water (two-photon spectrum) in combination with quasi-particle (QP) effects. The good performance of the GW/BSE methodology is also shown on large donor-acceptor-type molecules, demonstrating its reliability for finite systems where the screening effects are much lower than in periodic systems and a correct description of the long-range behaviour of the exchange-correlation functional is essential. In order to enhance the predictive power of the GW/BSE theory for molecular systems starting from self-interaction free orbitals, a many-body based screening mixing scheme is introduced which remarkably improves the agreement of calculated excitation energies with reference data. In the second part, non-adiabatic excited-state dynamics of condensed water is studied. A combination of ab-initio Born-Oppenheimer molecular dynamics and time-dependent density functional theory is applied. The complex proton dynamics is investigated by large-scale excited-state calculations. It is found that instantaneous concerted hops of protons to the neighboring water molecules (Grotthuss mechanism) are highly unlikely. Furthermore, the solvated electron formed upon proton transfer in the excited state is not fully localized within a cavity-like environment as a consequence of attractive interaction with the surrounding water molecules
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