Do you want to publish a course? Click here

Facile synthetic route to transition metal oxyfluorides via reactions between metal oxides and PTFE

61   0   0.0 ( 0 )
 Added by Daigorou Hirai
 Publication date 2018
  fields Physics
and research's language is English




Ask ChatGPT about the research

Inorganic oxyfluorides have significant importance in the development of new functionalities for energy production and storage, photonics, catalysis, etc. In order to explore a simple preparation route that avoids the use of toxic HF or F2 gas as a reaction reagent, we have employed polytetrafluoroethylene (PTFE). Five oxyfluorides including Nb5O12F, Nb3O7F, Ta3O7F, TaO2F, and Mo4O11.2F0.8 were synthesized by reactions between PTFE and transition metal oxides in sealed quartz ampules. The reaction mechanism was studied by means of gas analysis, which detected SiF4 as a main product gas during the reaction. A possible reaction mechanism between the PTFE and transition metal oxides is discussed.

rate research

Read More

The electronic structure in alkaline earth AeO (Ae = Be, Mg, Ca, Sr, Ba) and post-transition metal oxides MeO (Me = Zn, Cd, Hg) is probed with oxygen K-edge X-ray absorption and emission spectroscopy. The experimental data is compared with density functional theory electronic structure calculations. We use our experimental spectra of the oxygen K-edge to estimate the bandgaps of these materials, and compare our results to the range of values available in the literature.
We discuss the application of the Agapito Curtarolo and Buongiorno Nardelli (ACBN0) pseudo-hybrid Hubbard density functional to several transition metal oxides. ACBN0 is a fast, accurate and parameter-free alternative to traditional DFT+$U$ and hybrid exact exchange methods. In ACBN0, the Hubbard energy of DFT+$U$ is calculated via the direct evaluation of the local Coulomb and exchange integrals in which the screening of the bare Coulomb potential is accounted for by a renormalization of the density matrix. We demonstrate the success of the ACBN0 approach for the electronic properties of a series technologically relevant mono-oxides (MnO, CoO, NiO, FeO, both at equilibrium and under pressure). We also present results on two mixed valence compounds, Co$_3$O$_4$ and Mn$_3$O$_4$. Our results, obtained at the computational cost of a standard LDA/PBE calculation, are in excellent agreement with hybrid functionals, the GW approximation and experimental measurements.
Transition metal oxides (TMOs) are complex electronic systems which exhibit a multitude of collective phenomena. Two archetypal examples are VO2 and NdNiO3, which undergo a metal-insulator phase-transition (MIT), the origin of which is still under debate. Here we report the discovery of a memory effect in both systems, manifest through an increase of resistance at a specific temperature, which is set by reversing the temperature-ramp from heating to cooling during the MIT. The characteristics of this ramp-reversal memory effect do not coincide with any previously reported history or memory effects in manganites, electron-glass or magnetic systems. From a broad range of experimental features, supported by theoretical modelling, we find that the main ingredients for the effect to arise are the spatial phase-separation of metallic and insulating regions during the MIT and the coupling of lattice strain to the local critical temperature of the phase transition. We conclude that the emergent memory effect originates from phase boundaries at the reversal-temperature leaving `scars` in the underlying lattice structure, giving rise to a local increase in the transition temperature. The universality and robustness of the effect shed new light on the MIT in complex oxides.
The discovery of intrinsic magnetic topological order in $rm MnBi_2Te_4$ has invigorated the search for materials with coexisting magnetic and topological phases. These multi-order quantum materials are expected to exhibit new topological phases that can be tuned with magnetic fields, but the search for such materials is stymied by difficulties in predicting magnetic structure and stability. Here, we compute over 27,000 unique magnetic orderings for over 3,000 transition metal oxides in the Materials Project database to determine their magnetic ground states and estimate their effective exchange parameters and critical temperatures. We perform a high-throughput band topology analysis of centrosymmetric magnetic materials, calculate topological invariants, and identify 18 new candidate ferromagnetic topological semimetals, axion insulators, and antiferromagnetic topological insulators. To accelerate future efforts, machine learning classifiers are trained to predict both magnetic ground states and magnetic topological order without requiring first-principles calculations.
In order to estimate the reactivity of a large number of potentially complex heterogeneous catalysts while searching for novel and more efficient materials, physical as well as data-centric models have been developed for a faster evaluation of adsorption energies compared to first-principles calculations. However, global models designed to describe as many materials as possible might overlook the very few compounds that have the appropriate adsorption properties to be suitable for a given catalytic process. Here, the subgroup-discovery (SGD) local artificial-intelligence approach is used to identify the key descriptive parameters and constrains on their values, the so-called SG rules, which particularly describe transition-metal surfaces with outstanding adsorption properties for the oxygen reduction and evolution reactions. We start from a data set of 95 oxygen adsorption energy values evaluated by density-functional-theory calculations for several monometallic surfaces along with 16 atomic, bulk and surface properties as candidate descriptive parameters. From this data set, SGD identifies constraints on the most relevant parameters describing materials and adsorption sites that (i) result in O adsorption energies within the Sabatier-optimal range required for the oxygen reduction reaction and (ii) present the largest deviations from the linear scaling relations between O and OH adsorption energies, which limit the performance in the oxygen evolution reaction. The SG rules not only reflect the local underlying physicochemical phenomena that result in the desired adsorption properties but also guide the challenging design of alloy catalysts.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا