1T’ RexMo1−xS2–2H MoS2 Lateral Heterojunction for Enhanced Hydrogen Evolution Reaction Performance

Nguyen, Huong Thi Thanh; Adofo, Laud Anim; Yang, Sang‐Hyeok; Kim, Hyungjin; Choi, Soo Ho; Kirubasankar, Balakrishnan; Cho, Byeong Wook; Ben‐Smith, Andrew; Kang, Joohoon; Kim, Young‐Min; Kim, Soo Min; Han, Young‐Kyu; Kim, Ki Kang

doi:10.1002/adfm.202209572

Cited by 19 publications

(12 citation statements)

References 68 publications

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“…Based on the above analysis, we suggest that stable, low-dimensional LHSs demonstrate high HER performance. Furthermore, we have identified a few recently published experimental papers − that demonstrate that the LHS has been research-oriented for HER. However, the structures described in the current work are novel and have not yet been experimentally confirmed.…”

Section: Resultsmentioning

confidence: 99%

Enhanced Hydrogen Evolution Performance at the Lateral Interface between Two Layered Materials Predicted with Machine Learning

Pham

Kim

Min

et al. 2023

ACS Appl. Mater. Interfaces

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While economical and effective catalysts are required for sustainable hydrogen production, low-dimensional interfacial engineering techniques have been developed to improve the catalytic activity in the hydrogen evolution reaction (HER). In this study, we used density functional theory (DFT) calculations to measure the Gibbs free energy change (ΔG H) in hydrogen adsorption in two-dimensional lateral heterostructures (LHSs) MX2/M’X’2 (MoS2/WS2, MoS2/WSe2, MoSe2/WS2, MoSe2/WSe2, MoTe2/WSe2, MoTe2/WTe2, and WS2/WSe2) and MX2/M’X’ (NbS2/ZnO, NbSe2/ZnO, NbS2/GaN, MoS2/ZnO, MoSe2/ZnO, MoS2/AlN, MoS2/GaN, and MoSe2/GaN) at several different positions near the interface. Compared to the interfaces of LHS MX2/M’X’2 and the surfaces of the monolayer MX2 and MX, the interfaces of LHS MX2/M’X’ display greater hydrogen evolution reactivity due to their metallic behavior. The hydrogen absorption is stronger at the interfaces of LHS MX2/M’X’, and that facilitates proton accessibility and increases the usage of catalytically active sites. Here, we develop three types of descriptors that can be used universally in 2D materials and can explain changes in ΔG H for different adsorption sites in a single LHS using only the basic information of the LHSs (type and number of neighboring atoms to the adsorption points). Using the DFT results of the LHSs and the various experimental data of atomic information, we trained machine learning (ML) models with the chosen descriptors to predict promising combinations and adsorption sites for HER catalysts among the LHSs. Our ML model achieved an R 2 score of 0.951 (regression) and an F 1 score of 0.749 (classification). Furthermore, the developed surrogate model was implemented to predict the structures in the test set and was based on confirmation from the DFT calculations via ΔG H values. The LHS MoS2/ZnO is the best candidate for HER among 49 candidates considered using both DFT and ML models because it has a ΔG H of −0.02 eV on top of O at the interface position and requires only −171 mV of overpotential to obtain the standard current density (10 A/cm2).

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Section: Resultsmentioning

confidence: 99%

Enhanced Hydrogen Evolution Performance at the Lateral Interface between Two Layered Materials Predicted with Machine Learning

Pham

Kim

Min

et al. 2023

ACS Appl. Mater. Interfaces

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“…Nguyen et al showed that the heterophase boundary of 1T' Re x Mo 1-x S 2 -2H MoS 2 has superior catalytic performance compared with pure phase MoS 2 , ReS 2 , and Re x Mo 1-x S 2 as shown in Figure 11c. [103] They further showed sharp band bending at the heterophase boundary using the KPFM (see the middle panel in Figure 11c). The modulation of band structure at the heterophase boundary can enhance the catalytic activity of the boundary atoms.…”

Section: Heterophase Boundary Catalystsmentioning

confidence: 95%

mentioning

confidence: 99%

Engineering Active Sites of 2D Materials for Active Hydrogen Evolution Reaction

Kim

Lee

Ling

et al. 2023

Advanced Physics Research

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Hydrogen evolution reaction (HER) is a promising clean and sustainable energy source with zero carbon emissions. Numerous studies have been conducted with versatile low dimensional materials, and the development of highly active electrochemical catalysts for HER is one of the most important applications of the materials in these studies. Despite such extensive research, the physical origin of the active catalytic performance of low dimensional materials remains unclear, and is distinguished from that of classical transition metal‐based catalysts. Here, recent studies on the intrinsic catalytic activity of 2D semimetals are reviewed, particularly among transition metal dichalcogenides (TMDs), highlighting promising strategies for the design of materials to further enhance their catalytic performance. One attractive approach for active HER involves fabricating single‐atom catalysts in the framework of TMDs. The electrochemical reaction at a catalytic atom for hydrogen evolution has typically been described by the Sabatier principle. Recent studies have focused on optimizing the Gibbs free energy for hydrogen adsorption via down‐sizing, alloying, hybridizing, hetero‐structuring, and phase boundary engineering, mostly with TMDs. The unique advantages of TMDs and their derivatives for HER are summarized, suggesting promising research directions for the design of low dimensional electrochemical catalysts for efficient HER and their energy applications.

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“…2c and Table S1, ESI †). 19 The R ct of Ni 0.8 Fe 0.2 PS 3 decreased by a factor of 3.5, compared to that of pristine NiPS 3 . These results suggest that the optimized Ni to Fe ratio for the fastest OER kinetics is 0.8 : 0.2.…”

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confidence: 93%

Unraveling the surface self-reconstruction of Fe-doped Ni-thiophosphate for efficient oxygen evolution reaction

Kirubasankar¹,

Won²,

Choi³

et al. 2023

Chem. Commun.

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1T’ Re_xMo₁₋_xS₂–2H MoS₂ Lateral Heterojunction for Enhanced Hydrogen Evolution Reaction Performance

Cited by 19 publications

References 68 publications

Enhanced Hydrogen Evolution Performance at the Lateral Interface between Two Layered Materials Predicted with Machine Learning

Enhanced Hydrogen Evolution Performance at the Lateral Interface between Two Layered Materials Predicted with Machine Learning

Engineering Active Sites of 2D Materials for Active Hydrogen Evolution Reaction

Unraveling the surface self-reconstruction of Fe-doped Ni-thiophosphate for efficient oxygen evolution reaction

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