Suppression of Defect-Induced Quenching via Chemical Potential Tuning: A Theoretical Solution for Enhancing Lanthanide Luminescence

2019 ◽  
Vol 123 (17) ◽  
pp. 11151-11161 ◽  
Author(s):  
Xian Qin ◽  
Lei Shen ◽  
Liangliang Liang ◽  
Sanyang Han ◽  
Zhigao Yi ◽  
...  
Keyword(s):  
Chemical Potential ◽  
Theoretical Solution ◽  
Lanthanide Luminescence

Chemical potential and dimensions of chain molecules in athermal environments

1996 ◽  
Vol 89 (6) ◽  
pp. 1733-1754 ◽  
Author(s):  
FERNANDO ESCOBEDO ◽  
JUAN DE PABLO
Keyword(s):  
Chemical Potential ◽  
Chain Molecules

Growth Kinetics of Quantum Size ZnO Particles

1998 ◽  
Vol 536 ◽  
Author(s):  
E. M. Wong ◽  
J. E. Bonevich ◽  
P. C. Searson
Keyword(s):  
Growth Kinetics ◽  
Ostwald Ripening ◽  
Chemical Potential ◽  
Colloidal Suspensions ◽  
Green Emission ◽  
Blue Shift ◽  
Constant Current ◽  
Mass Model ◽  
Zno Particles ◽  
Kinetics Of

AbstractColloidal chemistry techniques were used to synthesize ZnO particles in the nanometer size regime. The particle aging kinetics were determined by monitoring the optical band edge absorption and using the effective mass model to approximate the particle size as a function of time. We show that the growth kinetics of the ZnO particles follow the Lifshitz, Slyozov, Wagner theory for Ostwald ripening. In this model, the higher curvature and hence chemical potential of smaller particles provides a driving force for dissolution. The larger particles continue to grow by diffusion limited transport of species dissolved in solution. Thin films were fabricated by constant current electrophoretic deposition (EPD) of the ZnO quantum particles from these colloidal suspensions. All the films exhibited a blue shift relative to the characteristic green emission associated with bulk ZnO. The optical characteristics of the particles in the colloidal suspensions were found to translate to the films.

Scalable Approach to High Coverages on Oxides via Iterative Training of a Machine-Learning Algorithm

2019 ◽  
Author(s):  
Andrew Medford ◽  
Shengchun Yang ◽  
Fuzhu Liu
Keyword(s):  
Machine Learning ◽  
Chemical Potential ◽  
Learning Algorithm ◽  
Absolute Error ◽  
Low Energy ◽  
Training Data ◽  
High Coverage ◽  
Metal Compounds ◽  
Adsorption Energies ◽  
The Stability

Understanding the interaction of multiple types of adsorbate molecules on solid surfaces is crucial to establishing the stability of catalysts under various chemical environments. Computational studies on the high coverage and mixed coverages of reaction intermediates are still challenging, especially for transition-metal compounds. In this work, we present a framework to predict differential adsorption energies and identify low-energy structures under high- and mixed-adsorbate coverages on oxide materials. The approach uses Gaussian process machine-learning models with quantified uncertainty in conjunction with an iterative training algorithm to actively identify the training set. The framework is demonstrated for the mixed adsorption of CH<sub>x</sub>, NH<sub>x</sub> and OH<sub>x</sub> species on the oxygen vacancy and pristine rutile TiO<sub>2</sub>(110) surface sites. The results indicate that the proposed algorithm is highly efficient at identifying the most valuable training data, and is able to predict differential adsorption energies with a mean absolute error of ~0.3 eV based on <25% of the total DFT data. The algorithm is also used to identify 76% of the low-energy structures based on <30% of the total DFT data, enabling construction of surface phase diagrams that account for high and mixed coverage as a function of the chemical potential of C, H, O, and N. Furthermore, the computational scaling indicates the algorithm scales nearly linearly (N<sup>1.12</sup>) as the number of adsorbates increases. This framework can be directly extended to metals, metal oxides, and other materials, providing a practical route toward the investigation of the behavior of catalysts under high-coverage conditions.

Intramolecular Proton Transfer in the Isomerization of Hydroxyacetone: A Detailed Characterization Based on Reaction Force Analysis and the Bond Fragility Spectrum

2020 ◽  
Author(s):  
Wallace Derricotte ◽  
Huiet Joseph
Keyword(s):  
Chemical Potential ◽  
Reaction Force ◽  
Intramolecular Proton Transfer ◽  
Intermediate Energy ◽  
Force Analysis ◽  
Activation Energy Barrier ◽  
Detailed Characterization ◽  
Proton Transfers ◽  
Reaction Force Constant

The mechanism of isomerization of hydroxyacetone to 2-hydroxypropanal is studied within the framework of reaction force analysis at the M06-2X/6-311++G(d,p) level of theory. Three unique pathways are considered: (i) a step-wise mechanism that proceeds through formation of the Z-isomer of their shared enediol intermediate, (ii) a step-wise mechanism that forms the E-isomer of the enediol, and (iii) a concerted pathway that bypasses the enediol intermediate. Energy calculations show that the concerted pathway has the lowest activation energy barrier at 45.7 kcal mol<sup>-1</sup>. The reaction force, chemical potential, and reaction electronic flux are calculated for each reaction to characterize electronic changes throughout the mechanism. The reaction force constant is calculated in order to investigate the synchronous/asynchronous nature of the concerted intramolecular proton transfers involved. Additional characterization of synchronicity is provided by calculating the bond fragility spectrum for each mechanism.

Structure, Stability and Water Adsorption on Ultra-Thin TiO2 Supported on TiN

2019 ◽  
Author(s):  
Jose Julio Gutierrez Moreno ◽  
Marco Fronzi ◽  
Pierre Lovera ◽  
alan O'Riordan ◽  
Mike J Ford ◽  
...  
Keyword(s):  
Density Functional ◽  
Water Adsorption ◽  
Chemical Potential ◽  
Energy Gap ◽  
Molecular Water ◽  
Structure Stability ◽  
Ambient Conditions ◽  
Rutile Structure ◽  
The Stability ◽  
The One

<p></p><p>Interfacial metal-oxide systems with ultrathin oxide layers are of high interest for their use in catalysis. In this study, we present a density functional theory (DFT) investigation of the structure of ultrathin rutile layers (one and two TiO<sub>2</sub> layers) supported on TiN and the stability of water on these interfacial structures. The rutile layers are stabilized on the TiN surface through the formation of interfacial Ti–O bonds. Charge transfer from the TiN substrate leads to the formation of reduced Ti<sup>3+</sup> cations in TiO<sub>2.</sub> The structure of the one-layer oxide slab is strongly distorted at the interface, while the thicker TiO<sub>2</sub> layer preserves the rutile structure. The energy cost for the formation of a single O vacancy in the one-layer oxide slab is only 0.5 eV with respect to the ideal interface. For the two-layer oxide slab, the introduction of several vacancies in an already non-stoichiometric system becomes progressively more favourable, which indicates the stability of the highly non-stoichiometric interfaces. Isolated water molecules dissociate when adsorbed at the TiO<sub>2</sub> layers. At higher coverages the preference is for molecular water adsorption. Our ab initio thermodynamics calculations show the fully water covered stoichiometric models as the most stable structure at typical ambient conditions. Interfacial models with multiple vacancies are most stable at low (reducing) oxygen chemical potential values. A water monolayer adsorbs dissociatively on the highly distorted 2-layer TiO<sub>1.75</sub>-TiN interface, where the Ti<sup>3+</sup> states lying above the top of the valence band contribute to a significant reduction of the energy gap compared to the stoichiometric TiO<sub>2</sub>-TiN model. Our results provide a guide for the design of novel interfacial systems containing ultrathin TiO<sub>2</sub> with potential application as photocatalytic water splitting devices.</p><p></p>

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