Deep vacancy induced low-density fluxional interfacial water

Liu, Keyang; Guo, Jianqing; Fu, Weizhong; Chen, Ji

doi:10.1103/physrevresearch.3.l042014

Cited by 2 publications

(1 citation statement)

References 51 publications

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“…For anatase (101), previous STM experiment suggested that water adsorbs molecularly on almost defect-free surface 16 or reduced surface with subsurface defects 17 in ultrahigh vacuum, but synchrotron radiation photoelectron spectroscopy 18 observed a water monolayer on the stoichiometric surface involves both molecular and dissociative adsorption, and X-ray diffraction experiments 19 also showed water dissociation on reduced surfaces with both ultrathin and bulk water. In simulations, BLYP MD 20 and DFT MD 21 with optB86b-vdW functional both predicted that bulk water adsorbs molecularly on (101) surface, while static DFT calculations with PBE functional showed the coexistence of dissociated and molecular water at monolayer coverage 22 . Recently, Andrade et al 23 used a combination of MLPs with SCAN functional and enhanced sampling MD, and predicted a water dissociation fraction of 5.6%.…”

Section: Introductionmentioning

confidence: 99%

Mechanistic insight on water dissociation on pristine low-index TiO2 surfaces from machine learning molecular dynamics simulations

Zeng,

Wodaczek,

Liu

et al. 2023

Nat Commun

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Water adsorption and dissociation processes on pristine low-index TiO2 interfaces are important but poorly understood outside the well-studied anatase (101) and rutile (110). To understand these, we construct three sets of machine learning potentials that are simultaneously applicable to various TiO2 surfaces, based on three density-functional-theory approximations. Here we show the water dissociation free energies on seven pristine TiO2 surfaces, and predict that anatase (100), anatase (110), rutile (001), and rutile (011) favor water dissociation, anatase (101) and rutile (100) have mostly molecular adsorption, while the simulations of rutile (110) sensitively depend on the slab thickness and molecular adsorption is preferred with thick slabs. Moreover, using an automated algorithm, we reveal that these surfaces follow different types of atomistic mechanisms for proton transfer and water dissociation: one-step, two-step, or both. These mechanisms can be rationalized based on the arrangements of water molecules on the different surfaces. Our finding thus demonstrates that the different pristine TiO2 surfaces react with water in distinct ways, and cannot be represented using just the low-energy anatase (101) and rutile (110) surfaces.

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Section: Introductionmentioning

confidence: 99%

Mechanistic insight on water dissociation on pristine low-index TiO2 surfaces from machine learning molecular dynamics simulations

Zeng,

Wodaczek,

Liu

et al. 2023

Nat Commun

Self Cite

View full text Add to dashboard Cite

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Review-Hysteresis in Carbon Nano-Structure Field Effect Transistor

Lin

Tsai

et al. 2022

Micromachines

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In recent decades, the research of nano-structure devices (e.g., carbon nanotube and graphene) has experienced rapid growth. These materials have supreme electronic, thermal, optical and mechanical properties and have received widespread concern in different fields. It is worth noting that gate hysteresis behavior of field effect transistors can always be found in ambient conditions, which may influence the transmission appearance. Many researchers have put forward various views on this question. Here, we summarize and discuss the mechanisms behind hysteresis, different influencing factors and improvement methods which help decrease or eliminate unevenness and asymmetry.

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Deep vacancy induced low-density fluxional interfacial water

Cited by 2 publications

References 51 publications

Mechanistic insight on water dissociation on pristine low-index TiO2 surfaces from machine learning molecular dynamics simulations

Mechanistic insight on water dissociation on pristine low-index TiO2 surfaces from machine learning molecular dynamics simulations

Review-Hysteresis in Carbon Nano-Structure Field Effect Transistor

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