CO Adsorbate Promotes Polaron Photoactivity on the Reduced Rutile TiO₂(110) Surface

Abstract

Polarons play a major role in determining the chemical properties of transition-metal oxides. Recent experiments show that adsorbates can attract inner polarons to surface sites. These findings require an atomistic understanding of the adsorbate influence on polaron dynamics and lifetime. We consider reduced rutile TiO 2 (110) with an oxygen vacancy as a prototypical surface and a CO molecule as a classic probe and perform ab initio adiabatic molecular dynamics, time-domain density functional theory, and nonadiabatic molecular dynamics simulations. The simulations show that subsurface polarons have little influence on CO adsorption and CO can desorb easily. On the contrary, surface polarons strongly enhance CO adsorption. At the same time, the adsorbed CO attracts polarons to the surface, allowing them to participate in catalytic processes with CO. The CO interaction with polarons changes their orbital origin, suppresses polaron hopping, and stabilizes them at surface sites. Partial delocalization of polarons onto CO decouples them from free holes, decreasing the nonadiabatic coupling and shortening the quantum coherence time, thereby reducing charge recombination. The calculations demonstrate that CO prefers to adsorb at the next-nearest-neighbor five-coordinated Ti 3+ surface electron polaron sites. The reported results provide a fundamental understanding of the influence of electron polarons on the initial stage of reactant adsorption and the effect of the adsorbate–polaron interaction on the polaron dynamics and lifetime. The study demonstrates how charge and polaron properties can be controlled by adsorbed species, allowing one to design high-performance transition-metal oxide catalysts.

Understanding Competitive Photo-Induced Molecular Oxygen Dissociation and Desorption Dynamics atop a Reduced Rutile TiO2(110) Surface: A Time-Domain Ab Initio Study

“…The decoherence-induced surface hopping algorithm was used because this approach incorporates decoherence correction in the current NA-MD simulations and captures the physical mechanism for the nucleus trajectory branching. The 1000 stochastic realizations of the surface hopping algorithm were set for each structure to guarantee good statistical convergence for NA-MD simulations using the Python extension for the ab initio dynamics code. , This approach has been used successfully to study the excited-state dynamics in a broad range of metal oxides. − …”

“…Although the DFT + U improves the bandgap, the obtained value is still smaller than the experimental data. Therefore, the “split operator” is used to scale the energy gap to the experimental value by adding appropriate constants to energy gaps by referring to our previous works. , The energy gap between the VBM and hole trap is also equally scaled. The NACs for each pair of states are changed accordingly given that the NAC is inversely proportional to the energy gap.…”

Structural Disorder in Higher-Temperature Phases Increases Charge Carrier Lifetimes in Metal Halide Perovskites

“…The ab initio NAMD simulations are performed using the decoherence-induced surface hopping (DISH) technique implemented within TDDFT in the Kohn–Sham (KS) framework. , Within the mixed quantum-classical dynamics approach, the lighter and faster electrons are treated quantum mechanically, and the heavier and slower nuclei are modeled semiclassically. , The destruction of superpositions formed between pairs of electronic states via NA coupling is regarded as decoherence. , The decoherence time is evaluated as the pure-dephasing time using the optical response theory. − Quantum transitions appear in the DISH algorithm as a result of the decoherence process and occur at decoherence effects, which provide the physical basis for hops . The method has been applied to study photoexcitation dynamics in a broad range of materials, including black phosphorus, , transition-metal dichalcogenides, − two-dimensional (2D) Ruddlesden–Popper and Dion–Jacobson perovskites, , lead halide perovskites containing dopants, , defects, ,,, isotopes, grain boundaries, and edge states, − interacting with water or oxygen molecules, ,, responding to strain and thermal effects, ,, etc. − …”

Strong Influence of the Anion Radius on the Passivation of Selenium Vacancy in Monolayer InSe: Insights from Time-Domain Ab Initio Analysis

“…Because the decoherence times calculated using the pure dephasing time in the optical response theory 32 are obviously shorter than charge trapping and recombination times, we consider the decoherence effect during the NAMD simulations. 33−35 The DISH approach has been applied to simulate the carrier dynamics in a large number of semiconductor materials, 36−43 including metallic oxides, 36,37 perovskites, 38−40 transition metal dichalcogenides, 41 and BP. 42,43 After the geometry optimization, five systems are heated to 300 K through velocity rescaling.…”

“…The NAMD simulations in pristine InSe (Figure a), V Se (Figure b), and passivated systems (Figure c) are carried out using the decoherence-induced surface hopping (DISH) method, which is implemented within the time-dependent Kohn–Sham density functional theory. , The heavier nuclei and lighter electrons are treated with (semi)­classical and quantum mechanics, respectively. Because the decoherence times calculated using the pure dephasing time in the optical response theory are obviously shorter than charge trapping and recombination times, we consider the decoherence effect during the NAMD simulations. − The DISH approach has been applied to simulate the carrier dynamics in a large number of semiconductor materials, − including metallic oxides, , perovskites, − transition metal dichalcogenides, and BP. , After the geometry optimization, five systems are heated to 300 K through velocity rescaling. Then, 6 ps microcanonical ensemble ( NVE ) MD trajectories are obtained for the NA electron–phonon coupling calculations, and 1000 initial configurations are selected for the NAMD simulations performed using the PYthon eXtension for Ab Initio Dynamics (PYXAID) software package.…”