Understanding the hydrogen evolution reaction activity of doped single-atom catalysts on two-dimensional GaPS4 by DFT and machine learning

[1]  Shengli Chen,et al.  Hydrogen bond network connectivity in the electric double layer dominates the kinetic pH effect in hydrogen electrocatalysis on Pt , 2022, Nature Catalysis.

[2]  Hongyan Zhao,et al.  Modeling the Potential-Dependent Kinetics of CO2 Electroreduction on Single-Nickel Atom Catalysts with Explicit Solvation , 2022, ACS Catalysis.

[3]  Xu Zhang,et al.  Accelerated Mining of 2D Van der Waals Heterojunctions by Integrating Supervised and Unsupervised Learning , 2022, Chemistry of Materials.

[4]  Lianping Wu,et al.  Data‐Driven High‐Throughput Rational Design of Double‐Atom Catalysts for Oxygen Evolution and Reduction , 2022, Advanced Functional Materials.

[5]  Jinjin Li,et al.  Vision for energy material design: a roadmap for integrated data-driven modeling , 2022, Journal of Energy Chemistry.

[6]  Tao Wang,et al.  Machine Learning-Assisted Screening of Stepped Alloy Surfaces for C1 Catalysis , 2022, ACS Catalysis.

[7]  P. Menezes,et al.  Functional role of single-atom catalysts in electrocatalytic hydrogen evolution: Current developments and future challenges , 2022, Coordination Chemistry Reviews.

[8]  L. Ricardez‐Sandoval,et al.  Machine Learning in Solid Heterogeneous Catalysis: Recent Developments, Challenges and Perspectives , 2021, Chemical Engineering Science.

[9]  Chengyou Liu,et al.  Catalytic mechanisms and practical activity of the active site in transition metal electrocatalysts for hydrogen evolution reaction , 2021, Chemical Engineering Journal.

[10]  Wei Yu,et al.  A density-functional-theory-based and machine-learning-accelerated hybrid method for intricate system catalysis , 2021, Materials Reports: Energy.

[11]  Yuting Luo,et al.  Synergistic Pt doping and phase conversion engineering in two-dimensional MoS2 for efficient hydrogen evolution , 2021, Nano Energy.

[12]  C. Xia,et al.  Cross‐Substitution Promoted Ultrawide Bandgap up to 4.5 eV in a 2D Semiconductor: Gallium Thiophosphate , 2021, Advanced materials.

[13]  Dachang Chen,et al.  Machine-learning-accelerated discovery of single-atom catalysts based on bidirectional activation mechanism , 2021, Chem Catalysis.

[14]  Lianping Wu,et al.  Machine learning-accelerated prediction of overpotential of oxygen evolution reaction of single-atom catalysts , 2021, iScience.

[15]  G. Moore,et al.  Anomalous collapses of Nares Strait ice arches leads to enhanced export of Arctic sea ice , 2021, Nature communications.

[16]  C. V. Singh,et al.  Exploring single atom catalysts of transition-metal doped phosphorus carbide monolayer for HER: A first-principles study , 2021, Journal of Energy Chemistry.

[17]  Vei Wang,et al.  VASPKIT: A user-friendly interface facilitating high-throughput computing and analysis using VASP code , 2019, Comput. Phys. Commun..

[18]  Edward F. Holby,et al.  Acid Stability and Demetalation of PGM-Free ORR Electrocatalyst Structures from Density Functional Theory: A Model for “Single-Atom Catalyst” Dissolution , 2020 .

[19]  An Chen,et al.  A Machine Learning Model on Simple Features for CO2 Reduction Electrocatalysts , 2020 .

[20]  Q. Yan,et al.  Promoting Electrocatalytic Hydrogen Evolution Reaction and Oxygen Evolution Reaction by Fields: Effects of Electric Field, Magnetic Field, Strain, and Light , 2020 .

[21]  Chenghua Sun,et al.  Enhancing hydrogen evolution of MoS2 basal planes by combining single-boron catalyst and compressive strain , 2020 .

[22]  Dehui Deng,et al.  Boosting hydrogen evolution on MoS2 via co-confining selenium in surface and cobalt in inner layer , 2020, Nature Communications.

[23]  A. Ramasubramaniam,et al.  Promoting Active Sites for Hydrogen Evolution in MoSe2 via Transition-Metal Doping , 2020 .

[24]  Ying Dai,et al.  Holey graphitic carbon nitride (g-CN) supported bifunctional single atom electrocatalysts for highly efficient overall water splitting , 2020 .

[25]  Zhaofu Zhang,et al.  Extrapolated Defect Transition Level in Two-dimensional Materials: The Case of Charged Native Point Defects in Monolayer Hexagonal Boron Nitride. , 2020, ACS applied materials & interfaces.

[26]  Wei Zhou,et al.  Scaling law of hydrogen evolution reaction for InSe monolayer with 3d transition metals doping and strain engineering , 2020, Journal of Energy Chemistry.

[27]  Mingwen Zhao,et al.  First-principles design of highly-efficient earth-abundant electrocatalysts for hydrogen evolution reaction: TiF3 and its analogs , 2019, Applied Surface Science.

[28]  Shiping Huang,et al.  Simultaneously Achieving High Activity and Selectivity toward Two-Electron O2 Electroreduction: The Power of Single-Atom Catalysts , 2019, ACS Catalysis.

[29]  A. Fontcuberta i Morral,et al.  Rational strain engineering in delafossite oxides for highly efficient hydrogen evolution catalysis in acidic media , 2019, Nature Catalysis.

[30]  Charlie Tsai,et al.  Enhancing Electrocatalytic Water Splitting by Strain Engineering , 2019, Advanced materials.

[31]  Tongtong Wang,et al.  Zn-doped MoSe2 nanosheets as high-performance electrocatalysts for hydrogen evolution reaction in acid media , 2019, Electrochimica Acta.

[32]  Jinlan Wang,et al.  Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning , 2018, Nature Communications.

[33]  S. Back,et al.  Suppression of Hydrogen Evolution Reaction in Electrochemical N2 Reduction Using Single-Atom Catalysts: A Computational Guideline , 2018, ACS Catalysis.

[34]  Nathan C Frey,et al.  Prediction of Enhanced Catalytic Activity for Hydrogen Evolution Reaction in Janus Transition Metal Dichalcogenides. , 2018, Nano letters.

[35]  Y. Jiao,et al.  Strain Effect in Bimetallic Electrocatalysts in the Hydrogen Evolution Reaction , 2018 .

[36]  R. Ma,et al.  Auto-optimizing Hydrogen Evolution Catalytic Activity of ReS2 through Intrinsic Charge Engineering. , 2018, ACS nano.

[37]  Ho Won Jang,et al.  Hydrogen Evolution Reaction at Anion Vacancy of Two-Dimensional Transition-Metal Dichalcogenides: Ab Initio Computational Screening. , 2018, The journal of physical chemistry letters.

[38]  B. Wood,et al.  Graphene Defects Trap Atomic Ni Species for Hydrogen and Oxygen Evolution Reactions , 2018 .

[39]  A. Du,et al.  Endohedral metallofullerenes (M@C60) as efficient catalysts for highly active hydrogen evolution reaction , 2017 .

[40]  Mingwei Chen,et al.  Coral-Shaped MoS2 Decorated with Graphene Quantum Dots Performing as a Highly Active Electrocatalyst for Hydrogen Evolution Reaction. , 2017, ACS applied materials & interfaces.

[41]  Ravishankar Sundararaman,et al.  Grand canonical electronic density-functional theory: Algorithms and applications to electrochemistry. , 2017, The Journal of chemical physics.

[42]  A. Du,et al.  2D MXenes: A New Family of Promising Catalysts for the Hydrogen Evolution Reaction , 2017 .

[43]  M. Weeda,et al.  The hydrogen economy – Vision or reality? , 2015 .

[44]  Haotian Wang,et al.  Transition-metal doped edge sites in vertically aligned MoS2 catalysts for enhanced hydrogen evolution , 2015, Nano Research.

[45]  Y. Najjar.  Hydrogen safety: The road toward green technology , 2013 .

[46]  Chandima Gomes,et al.  Hydrogen as an energy carrier: Prospects and challenges , 2012 .

[47]  Xiaofeng Yang,et al.  Single-atom catalysis of CO oxidation using Pt1/FeOx. , 2011, Nature chemistry.

[48]  J. A. Alonso,et al.  Chemical Properties of Small Au Clusters: An Analysis of the Local Site Reactivity , 2007 .

[49]  Stefan Grimme,et al.  Semiempirical GGA‐type density functional constructed with a long‐range dispersion correction , 2006, J. Comput. Chem..

[50]  G. Henkelman,et al.  A fast and robust algorithm for Bader decomposition of charge density , 2006 .

[51]  Thomas Bligaard,et al.  Trends in the exchange current for hydrogen evolution , 2005 .

[52]  G. Scuseria,et al.  Hybrid functionals based on a screened Coulomb potential , 2003 .

[53]  Robert G. Parr,et al.  Variational Principles for Describing Chemical Reactions: The Fukui Function and Chemical Hardness Revisited , 2000 .

[54]  G. Scuseria,et al.  Assessment of the Perdew–Burke–Ernzerhof exchange-correlation functional , 1999 .

[55]  Richard Dronskowski,et al.  Crystal orbital Hamilton populations (COHP): energy-resolved visualization of chemical bonding in solids based on density-functional calculations , 1993 .

[56]  S. Nosé.  A unified formulation of the constant temperature molecular dynamics methods , 1984 .